Cloud computing has become an essential technology for businesses and individuals, providing a flexible and scalable way to store, process and access data and applications. As cloud usage continues to grow, there is a...
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In the modern era of living a fast lifestyle, people are not more conscious of their food eating and lifestyle. Due to these reasons, the chances of having a cardiac-related disease have risen drastically. This paper ...
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Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental condition worldwide, including in Bangladesh. Children with ADHD encounter difficulties in sustaining attention, impaired executive fun...
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E-learning systems improve day by day. Therefore, it is important to monitor and evaluate student performance to provide targeted content. This paper focuses on a model for intelligent E-learning systems that can iden...
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At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhance...
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At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system ***,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative *** addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the SPSS tool,and respective graphical illustrations were *** results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten *** in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved *** EDLA algorithm introduces novelty concerning its performance and particular activation *** proposed method will be utilized effectively in brain tumor detection in a precise and accurate *** algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses *** the quantity of dataset records is enormous,then themethod’s computation power has to be updated.
The primary goals of smart cities are efficiently managing the rapid urbanization process, energy consumption, environmental protection, citizen economic and living standards, and people's capacity to utilize and ...
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Both manual (relating to the use of hands) and non-manual markers (NMM), such as facial expressions or mouthing cues, are important for providing the complete meaning of phrases in American Sign Language (ASL). Effort...
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The term "heart or cardiovascular disease" is frequently used to refer to a variety of heart-related issues. It is one of the illnesses with the highest mortality rate. Its fatality rate results in nearly 17...
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In recent years, cyber-attacks have become more frequent and advanced, targeting critical infrastructure, businesses, homes, and government agencies. Detecting and preventing these attacks at the earliest stage possib...
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This paper focuses on the challenges of modeling and verifying symmetric distributed algorithms with point-to-point and bidirectional communications using the SPIN model checker. In this paper, we first state the prob...
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