Recent Trends in Parallel Computing
Volume 11, Issue 2 (2024)
Table of contents
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Navigating Privacy and Security in Cloud Computing
Abstract: Cloud computing has rapidly evolved, serving as a cornerstone for storage, information processing, and various applications. Its adoption has surged across enterprises and small businesses alike, offering them efficient means to store and process data. However, alongside its undeniable benefits, the cloud also presents inherent risks to privacy and security, as data traverses and resides on remote servers. Employing tactics such as data encryption, multifactor authentication, access control, and intrusion …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Advancements, Hurdles, and Applications in Quantum Computing
Abstract: Using the ideas of quantum mechanics, quantum computing has become a paradigm shift in computing, enabling computations to be completed tenfold quicker than with traditional computers. This study investigates the current status of quantum computing, looking at the notable advancements, ongoing difficulties, and potential uses that could completely change a range of industries. By utilizing the principles of superposition and entanglement, quantum computers can potentially solve complex problems that classical …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 11–29 Read article
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A Review Paper on Attendance Tracking System Using Cloud Computing
Abstract: Attendance monitoring systems are critical in educational institutions and organizations for maintaining accurate records of student or staff attendance. In contrast, traditional methods frequently rely on manual processes, which are not only time-consuming but also susceptible to errors. To overcome these issues, this work suggests an innovative Attendance Tracking System based on Cloud Computing and Artificial Intelligence (AI). The technology uses powerful AI algorithms for facial recognition, allowing for automated …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 30–35 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Rise of Python: Analyzing Its Dominance in 2023 Programming Trends
Abstract: The study is on how Python rose as a leading programming language in 2023 and what are the top reasons of this ubiquitous utilization among industries. The Python programming language has been a go-to choice for both beginners and developers alike, courtesy of its versatility in working over various domains like Data Science, Machine Learning Web Development Automation etc. By having a vast library and framework ecosystem, supported by popular …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 43–47 Read article