Crowd counting is a computer vision task that focuses on accurately estimating the number of people present in a given scene. In the past few years, convolutional neural network-based deep learning techniques have ach...
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Effective dissemination of information to audience in institutions of higher learning is a critical challenge in today's interconnected world. Conveying timely information to every individual can be arduous due to...
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Measuring Hemoglobin (Hb) levels is required for the assessment of different health conditions, such as anemia, a condition where there are insufficient healthy red blood cells to carry enough oxygen to the body’s ti...
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The paper presents a scaled laboratory experimental model of ferroresonant circuit designed for detailed investigation of the ferroresonance phenomena. To enable accurate ferroresonance examination, the system is expa...
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Both the academic and industry begin the early research on the network architectures of the 6th generation (6G) mobile communication system, which integrates the satellite networks for ubiquitous access. However, the ...
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Involving subject matter experts in prompt engineering can guide LLM outputs toward more helpful, accurate, and tailored content that meets the diverse needs of different domains. However, iterating towards effective ...
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We report the next generation optical nanotweezer approaches employing plasmatic cavities and optical anapole states for the high throughput trapping and dynamic manipulation of nanoscale objects and biomolecules with...
Nowadays, energy efficiency for buildings is considered one of the most valuable solutions to provide services sustainably. Many buildings are designed aiming to consume less energy while performing the required tasks...
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Automated agriculture processing system are the need of today as food manufacturing industries are suffering great loss on part of defective vegetables and fruits. Many researches are working to develop an automated s...
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Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the *** learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and securit...
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Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the *** learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and security *** is crucial in offering a proactive security system in the field of *** real time,cybersecurity protects information,information systems,and networks from *** the recent decade,several assessments on security and privacy estimates have noted a rapid growth in both the incidence and quantity of cybersecurity *** an increasing rate,intruders are breaching information *** detection,software vulnerability diagnosis,phishing page identification,denial of service assaults,and malware identification are the foremost cyber-security concerns that require efficient *** have tried a variety of approaches to address the present cybersecurity obstacles and *** a similar vein,the goal of this research is to assess the idealness of machine learning-based intrusion detection systems under fuzzy conditions using a Multi-Criteria Decision Making(MCDM)-based Analytical Hierarchy Process(AHP)and a Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS).Fuzzy sets are ideal for dealing with decision-making scenarios in which experts are unsure of the best course of *** projected work would support practitioners in identifying,prioritising,and selecting cybersecurityrelated attributes for intrusion detection systems,allowing them to design more optimal and effective intrusion detection systems.
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