While large language models (LLMs) show promise for various tasks, their performance in compound aspect-based sentiment analysis (ABSA) tasks lags behind fine-tuned models. However, the potential of LLMs fine-tuned fo...
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With multiple waves of epidemics devastating the global population and the possibility of future waves looming large, testing has moved to the centre-stage of epidemic management. In this study, we explore how offerin...
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ISBN:
(数字)9798350358513
ISBN:
(纸本)9798350358520
With multiple waves of epidemics devastating the global population and the possibility of future waves looming large, testing has moved to the centre-stage of epidemic management. In this study, we explore how offering incentives for testing during epidemics can encourage people to test themselves responsibly, without having to resort to strict penalties for noncompliance. We use a scientific approach to examine how adjusting testing costs can influence people’s behavior during outbreaks. We compare two scenarios: one where testing decisions are centrally managed for maximum social benefit, and another where individuals make their own testing choices. For achieving computational tractability in analyzing a large population, we use the mean field approach. By combining ideas from optimal control theory and mean field game theory, we investigate how policymakers can use subsidies to motivate people to test more responsibly during epidemics. This research offers valuable insights for policymakers on the quantum of subsidies needed to encourage desirable testing behavior of rational individuals in a population.
Symbolic learning is the subfield of machine learning concerned with learning predictive models with knowledge represented in logical form, such as decision tree and decision list models. Ensemble learning methods, su...
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A method for detecting and monitoring the long-term time course of brain processes is described for two different conditions: i) A abbreviated version of a visual problem-solving IQ (Intelligent Quotient) Raven test a...
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The study investigates the accuracy of CST simulations in TEM mode and unit cell simulations for determining the refractive index (n) of materials. The results in TEM mode align with the expected properties of air, af...
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Nowadays, the risk estimators are to be applied based on the population characteristics of their country, which is termed as race attribute. There were specific tools to determine the risk of cardiovascular disease. A...
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ISBN:
(数字)9798331522667
ISBN:
(纸本)9798331522674
Nowadays, the risk estimators are to be applied based on the population characteristics of their country, which is termed as race attribute. There were specific tools to determine the risk of cardiovascular disease. Among many diseases, the mortality rate of the people is increasing due to a lack of quality lifestyle. In order to provide a guide to the individual based on their specific characteristics and lifestyle, would classify the risk into specific categories like severe (High), Moderate, and normal(Low) with pre-defined threshold constraints. The risk assessment estimators alert the individual to control certain modifiable attributes irrespective of their non-modifiable elements. The integration of random forests and intelligent rule mining would generate the CVD risk prediction. Efficiency as well as interpretability are important in this competitive hybrid model. The ultimate benefits assured are extending the lives of the patients by knowing the importance of daily work, habits, and their control food, presenting a powerful opportunity by practicing better personalization monitoring and improved patient care, and improved informed decisions for immediate action. The early prevention initiation by identifying the risk severity optimizes follow-up of better practices and treatment styles, resulting in improved decision making for better health care of the individual.
A correct CVD diagnosis and outcome, on the other hand, result in expedited patient care and highly accurate treatment, as well as good results. Medicine has turned to machine learning since it is capable of discernin...
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The human brain is made up of millions of neurons, each of which plays a crucial part in directing the behaviour of the human body in response to internal/external motor-impulses. These neurons will act as data condui...
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Currently, electric vehicle (EV) battery platforms typically vary in standard, commonly rated at either 800V or 400V. Conventional wireless charging system (WCS) are limited to single voltage level charging, necessita...
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In this paper, a model predictive robust control (MPRC) is proposed for a three-phase capacitive-coupling grid-connect inverter (CGCI) to improve the power quality compensation performance under deviating system param...
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