Real time object detection in traffic surveillance is one of the latest topics in today's world using Region based Convolutional Neural Networks algorithm in comparison with Convolutional Neural Networks. Real-Tim...
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In this paper, focusing on the health of people posted on Twitter, we propose a method for determining urgency and disease using morpheme analysis of natural language processing model Bert and morpheme analysis tool J...
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Information security is one of the most important things in the science of security, and data and information encryption are essential parts of it. In this paper, we will talk about a new type of encryption called Usi...
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This Health-related problem is now seen as crucial to people that smart health care is developing to address them. Information and Communication Technologies (ICT) will give reasonable solutions in healthcare, educati...
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In recent times, plagiarism of handwritten assignments has been rampant. Deep Learning models such as Convolutional Neural Networks have proven to be resourceful for recognition tasks in computer vision. Additionally,...
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The discovery of fake reviews is one of the major concerns for the E-commerce business-the Consumers on reviews before finalizing their choice for the product. The authenticity of online reviews is influential for e-c...
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Application domain of Unmanned Aerial Vehicles(UAVs) expands every day. Multiple of these devices can simply be put together to form versatile and powerful Mobile ad hoc Networks (MANETs). Unfortunately, the existing ...
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Object detection and Tracking are important tasks in both moving and static camera applications like unmanned vehicles, human-assisted vehicles, product parts inspection, video surveillance, and many more. These appli...
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Coronary Artery Disease (CAD) is a significant global health issue that requires reliable and prompt prediction approaches. This research proposes an innovative approach to improvise CAD prediction by implementing dif...
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ISBN:
(数字)9798350371680
ISBN:
(纸本)9798350371697
Coronary Artery Disease (CAD) is a significant global health issue that requires reliable and prompt prediction approaches. This research proposes an innovative approach to improvise CAD prediction by implementing different machine learning algorithms like Support Vector Machine (SVM), Logistic Regression, Random Forest and KNN [5]. To deal with the mixed types of data, FAMD is incorporated. It is used for dimensionality reduction purpose addressing the complexities of a mixed dataset comprising both categorical and numerical variables. We applied all these machine learning algorithms without reducing the dataset and evaluated the accuracy, precision, recall and f1-score of all the algorithms. After that, we reduced the dataset with the help of FAMD and than again applying all those included algorithms on the reduced dataset and calculated the accuracy, precision, recall and f1-score. All these included algorithms without the application of FAMD and with the application of FAMD undergo a comparative analysis to distinguish their performances in CAD prediction. With the help of the compaprative analysis, it is discovered that the results of the models are improved and better with the application of FAMD than without FAMD.
This paper presents a system of two-hop hybrid communication system that uses a decode and forward relaying to share the data between source and destination. The radio channel is modeled through η-μ fading distribut...
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