Ayurvedic herbs hold immense importance in traditional Ayurvedic medicine. These herbs are considered vital elements in maintaining physical, mental, and spiritual balance in the human body. According to ayurveda, dis...
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A framework known as optical character recognition is capable of converting handwritten or printed pictures into machine-editable structures. Several Indian dialects, including Hindi, Nepali, Marathi, Sindhi, and othe...
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As a new and potentially devastating form of cyberattack, ‘Phishing’ URLs pose a risk to users by impersonating legitimate websites in an effort to obtain sensitive information such as usernames, passwords, and fina...
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The right partner and high innovation speed are crucial for a successful research and development (R&D) alliance in the high-tech industry. Does homogeneity or heterogeneity between partners benefit innovation spe...
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Diabetes affects more than half a million individuals globally. Diabetes can cause heart attacks, renal damage, and even blindness. Machine learning algorithms, with their intelligence capacity can precisely anticipat...
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Highly over-parameterized neural networks have the ability to completely shatter the entire dataset. Despite their huge capacity, over-parameterized networks show strong algorithmic stability. In cases where semantic ...
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The Music to Score Conversion (MSC) project focuses on bridging the gap between auditory and visual representations of music. It uses signal processing techniques for the conversion such as pitch estimation, onset det...
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We propose to find optimal value of refresh time of fault tolerant k-edge connected mobile ad-hoc networks. For study the FGSS algorithm is taken for topology control. The algorithm runs periodically on individual nod...
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The traditional system of issue reporting has heavily relied on manual processes that require users to register their complaints with the authorities. This method is time-consuming and often results in inefficiencies ...
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ISBN:
(数字)9798350350357
ISBN:
(纸本)9798350350364
The traditional system of issue reporting has heavily relied on manual processes that require users to register their complaints with the authorities. This method is time-consuming and often results in inefficiencies due to the lack of a centralized and transparent mechanism. Our idea revolutionizes the traditional approach by employing a cutting-edge solution that grants users the ability to report and track issues directly and effectively, paving the way for a new era of seamless and transparent issue reporting. The latest technological advancements encourage the convergence of various technologies, seamlessly integrating application development, machine learning features, and cloud computing.
The static nature of cyber defense systems gives attackers a sufficient amount of time to explore and further exploit the vulnerabilities of information technology *** this paper,we investigate a problem where multiag...
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The static nature of cyber defense systems gives attackers a sufficient amount of time to explore and further exploit the vulnerabilities of information technology *** this paper,we investigate a problem where multiagent sys-tems sensing and acting in an environment contribute to adaptive cyber *** present a learning strategy that enables multiple agents to learn optimal poli-cies using multiagent reinforcement learning(MARL).Our proposed approach is inspired by the multiarmed bandits(MAB)learning technique for multiple agents to cooperate in decision making or to work *** study a MAB approach in which defenders visit a system multiple times in an alternating fash-ion to maximize their rewards and protect their *** find that this game can be modeled from an individual player’s perspective as a restless MAB *** discover further results when the MAB takes the form of a pure birth process,such as a myopic optimal policy,as well as providing environments that offer the necessary incentives required for cooperation in multiplayer projects.
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