Artificial Intelligence techniques based on Machine Learning algorithms, Neural Networks and Naïve Bayes can optimise the diagnostic process of the SARS-CoV-2 or Covid-19. The most significant help of these techn...
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In recent years, several studies have reported the potential of employing digital games in EFL (English as Foreign Language) courses to promote students' learning motivation. However, scholars have pointed out tha...
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In recent years, several studies have reported the potential of employing digital games in EFL (English as Foreign Language) courses to promote students' learning motivation. However, scholars have pointed out that students generally lack self-learning ability, which is the key to the success of learning a foreign language. Therefore, it is crucial to foster students' self-learning ability during the game-based learning process. In this study, an expert system was developed to facilitate self-regulated learning in digital game-based learning contexts. To evaluate the effectiveness of the proposed approach, a quasi-experimental design was employed in a university English course. The experimental group students learned with the self-regulated English vocabulary game (SR-EVG) approach, while the control group students learned with the conventional English vocabulary game (C-EVG) approach. The experimental results indicated that the use of the SR-EVG approach could improve learners' English vocabulary achievement and self-regulation compared with the C-EVG approach without increasing students' English learning anxiety. Moreover, through qualitative interviews, it was found that students who used the SR-EVG approach would focus on their learning due to goal-setting in the game and would pay more attention to the learning strategies they used. Practitioner notes: What is already known about this topic Digital game-based learning situates students in a realistic situational environment, enabling students to learn by experiencing and interacting with the situations. Without appropriate scaffolding during digital game-based learning, students may become overly focused on the game, or perform many non-learning behaviors Self-regulated learning refers to students’ ability to learn on their own via goal setting, strategic planning, self-monitoring, and self-adjustment. What this paper adds An expert system-guided self-regulated learning approach was proposed to facilitate EFL s
Coral-like structures of the Y_(3-x)Pr_(x)Fe_(5-y)Yb_(y)O_(12),(0.00 ≤ x ≤ 0.04, 0.00 ≤ y ≤ 0.02) compound were synthesized using the sol-gel method. Structural investigation certified the YIG cubic crystal struct...
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Coral-like structures of the Y_(3-x)Pr_(x)Fe_(5-y)Yb_(y)O_(12),(0.00 ≤ x ≤ 0.04, 0.00 ≤ y ≤ 0.02) compound were synthesized using the sol-gel method. Structural investigation certified the YIG cubic crystal structure formation, without any secondary phase. It is shown that, the relatively large ionic radius of the dopant cations results in an expansion of the lattice parameter, variations in the Iona-O-Iondangle, Iona-O,Iond-O and Ionc-O bond distances and decrease in the average crystallite size. Fourier transform infrared(FTIR) and Raman measurements are essential to testify the single-phase formation of YIG crystal structure and are observed changes in the stretching and vibrational modes, respectively. The morphological study, energy dispersive spectroscopy(EDS) spectra and textural properties show corallike structures, peaks associated with Pr^(3+) and Yb^(3+) atoms and the effect of dopants on surface area,diameter, and pore volume, respectively. The optical analysis from diffuse reflectance spectra witnessed an increase in the optical gap band, a decrease in Urbach energy and blue shift in the charge transfer,correlated with the expansion of the unit cell due to the dopant's insertion in the YIG structure. A typical ferrimagnetic behavior is exhibited by the Y_(3-x)Pr_(x)Fe_(5-y)Yb_(y)O_(12)compound. The saturation magnetization(M_(s)), cubic anisotropy constant(K_(1)) and coercive field(H_(c)) increase with the Pr^(3+)cations content, as consequence of their magnetic nature and distribution around of Fe^(3+)ions due to the coexistence with the Yb^(3+). Finally, for the first time, antibacterial tests by mean of the direct contact method were performed for YIG co-doped with Pr^(3+)and Yb^(3+)and it is shown that, relatively high dosages of Pr^(3+) cations favored the activity against S. aureus, therefore, a new biological property for YIG doped with rare earths is presented.
This study investigates the effectiveness and feasibility of using parallel machines with GPUs of different capacities to train large language models (LLMs) as an alternative to costly cloud platforms. The study explo...
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ISBN:
(数字)9798331513054
ISBN:
(纸本)9798331513061
This study investigates the effectiveness and feasibility of using parallel machines with GPUs of different capacities to train large language models (LLMs) as an alternative to costly cloud platforms. The study explores optimization techniques focused on data, models, budget, and systems, detailing the configuration of a multi-GPU architecture and its implementation with CUDA software, PyTorch, and the HetSeq library, adapted to maximize performance in heterogeneous systems, including the usage of legacy resources (e.g., older GPUs). In performance tests, three approaches are compared: homogeneous load distribution, heterogeneous distribution, and HetSeq usage. The HetSeq configuration yielded a substantial performance improvement, achieving an execution time of 129,759 seconds, significantly lower than the 153,175 seconds observed for the homogeneous configuration and 165,387 seconds for the heterogeneous configuration in the maximum setup tested, representing a reduction of 15% and 21%, respectively. These results highlight HetSeq's advantage in optimizing training time as more GPUs are added, outperforming traditional approaches that attempt to standardize hardware utilization, such as PyTorch. Further analysis using Amdahl's Law reveals that approximately 82% of the training process is parallelizable, underscoring that optimized heterogeneous architectures are both viable and economically advantageous in scenarios that do not require homogeneous hardware.
Startups arise in environments of extreme uncertainty, with few resources and the need to scale quickly. In the growth phase, they still need agility, but they tend to concern more with software quality and the develo...
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This paper presents an event-driven cloud-based serverless architecture for a remote patient monitoring system. The architecture is designed to be scalable, resilient, and cost-effective, and leverages managed cloud s...
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ISBN:
(数字)9798331533366
ISBN:
(纸本)9798331533373
This paper presents an event-driven cloud-based serverless architecture for a remote patient monitoring system. The architecture is designed to be scalable, resilient, and cost-effective, and leverages managed cloud services to handle load variations and service faults. To evaluate the architecture, we conducted comprehensive capacity, scalability, and resilience tests. The test results show that the architecture can meet the performance, scalability, and reliability requirements of a remote patient monitoring system. Additionally, a detailed analysis of operational costs in the cloud confirms the cost-effectiveness of the solution and highlights practical opportunities for improvements.
Human hearing is an important sense, which complements the other senses, and is essential for children to begin to acquire basic concepts of the world;however, in severe cases of disability, children become marginaliz...
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Equipment monitoring for failure prediction is receiving attention from different sectors of society, such as industry, healthcare, and defense. In the defense domain, assets like military vehicles generate data that ...
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The recent integration of visual capabilities into Large Language Models (LLMs) has the potential to play a pivotal role in science and technology education, where visual elements such as diagrams, charts, and tables ...
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Smart Government initiatives aim to enhance governmental services by strategically applying digital technologies. Property tax assessment, a crucial aspect of government revenue, often faces challenges due to outdated...
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ISBN:
(数字)9798350364316
ISBN:
(纸本)9798350364323
Smart Government initiatives aim to enhance governmental services by strategically applying digital technologies. Property tax assessment, a crucial aspect of government revenue, often faces challenges due to outdated methods and complex evaluation models. The procedures to estimate property values are time consuming since mass estimation must evaluate dozens of building features, some of which may not completely influence market values. For government appraisers, making sense of millions of spatial data is cumbersome and prone to error. This paper proposes a comprehensive framework integrating Machine Learning (ML), dashboards, and Geographic Information Systems to address these challenges. By leveraging ML algorithms, interactive dashboards, and geospatial data, tax agencies can streamline property assessment processes, improve accuracy, and facilitate real-time decision-making. A case study in Fortaleza, Brazil, demonstrates the framework's effectiveness in enhancing land value assessment and property taxation within the Smart Governance context. This paper provides insights into the benefits and challenges of implementing such a framework and underscores its potential to revolutionize property tax assessment practices.
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