Many multilingual communities, including numerous in Africa, frequently engage in code-switching during conversations. This behaviour stresses the need for natural language processing technologies adept.at processing ...
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As the world's internet user base approaches 5.3 billion by 2023, the demand for bandwidth is only growing. The paper highlights the importance of wavelength division multiplexing passive optical networks (WDM-PON...
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Wireless Sensor Networks (WSNs) are highly implemented in harsh and dynamic environments. In such configurations, faults and anomalies easily occur, causing unwanted disruptions in data accuracy and network performanc...
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One of the most important aspects of data forecasting is selecting the most promising algorithm to model and predict a specific phenomenon. As with other data mining jobs, forecasting (or prediction) selects the optim...
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Exploiting parallelism to train deep learning models requires GPUs to cooperate through collective communication primitives. While systems like DGX, equipped with proprietary interconnects, have been extensively studi...
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Internet addiction is becoming one of the critical issues among teenagers and young university students. This habit not only negatively impacts the student's learning performance, but also affects the student'...
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Both consumers and healthcare providers have benefited greatly from the quick development of software-based technology. The dominance of blockchains is impending as the medical care sector moves quickly towards digiti...
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Artificial intelligence (AI) advancements have opened new avenues in medical diagnostics, particularly for the early detection of respiratory conditions such as Chronic Obstructive Pulmonary Disease (COPD). COPD, the ...
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Artificial intelligence (AI) breakthroughs have created new opportunities in the field of medical diagnostics, especially for the early identification of respiratory conditions like Chronic Obstructive Pulmonary Disea...
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Amplification by subsampling is one of the main primitives in machine learning with differential privacy (DP): Training a model on random batches instead of complete datasets results in stronger privacy. This is tradi...
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