Landscape analysis has received increasing attention in the literature, with a major focus on producing feature data to be used in a machine learning pipeline for automatic algorithm selection and configuration. In co...
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Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic *** have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volu...
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Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic *** have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs *** clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature *** goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)*** final review included 133 *** research themes include question quality,answer quality,and expert *** terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack *** scope of most articles was confined to just one platform with few cross-platform *** with ML outnumber those with ***,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.
In today's digital landscape, the task of identifying various types of malicious files has become progressively challenging. Modern malware exhibits increasing sophistication, often evading conventional anti-malwa...
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This work analyzes the possibility of reducing the energy consumption of digital-to-analog converters by minimizing the energy consumption of the elements that ensure their operation. Due to the fact that such decisio...
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This article presents an automated system for infrared thermography of biological tissues. The purpose of the system development is to provide noninvasive and rapid temperature measurements of biological tissues. The ...
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Cross-Site Scripting (XSS) is one of the most grievous vulnerabilities-a pitfall through which web applications are affected. These types of attacks are complex, and the available threat landscape is always changing, ...
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In today's world, the traditional way of password based authentication is having limitations in addressing the security concerns of the digital users. There is a strong movement in favour of passwordless authentic...
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The process of learning new programming languages sometimes involves the transfer of knowledge from previously learned languages. While knowledge transfer can facilitate quicker learning and enhance problem-solving ef...
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Heart disease is a leading cause ofmortality ***(ECG)play a crucial role in diagnosing heart ***,interpreting ECGsignals necessitates specialized knowledge and *** development of automated methods for ECG analysis has...
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Heart disease is a leading cause ofmortality ***(ECG)play a crucial role in diagnosing heart ***,interpreting ECGsignals necessitates specialized knowledge and *** development of automated methods for ECG analysis has the potential to enhance the accuracy and efficiency of heart disease *** research paper proposes a 3D Convolutional Long Short-Term Memory(Conv-LSTM)model for detecting heart disease using ECG *** proposed model combines the advantages of both convolutional neural networks(CNN)and long short-term memory(LSTM)*** considering both the spatial and temporal dependencies of ECG,the 3D Conv-LSTM model enables the detection of subtle changes in the signal over *** model is trained on a dataset of ECG recordings from patients with various heart conditions,including arrhythmia,myocardial infarction,and heart *** results show that the proposed 3D Conv-LSTM model outperforms traditional 2D CNN models in detecting heart disease,achieving an accuracy of 88%in the classification of five ***,themodel outperforms the other state-of-the-art deep learning models for ECG-based heart disease ***,the proposedConv-LSTMnetwork yields highly accurate outcomes in identifying abnormalities in specific ECG *** proposed 3D Conv-LSTM model holds promise as a valuable tool for automated heart disease detection and *** study underscores the significance of incorporating spatial and temporal dependencies in ECG-based heart disease *** highlights the potential of deep-learning models in enhancing the accuracy and efficiency of diagnosis.
Students are excellent at making make up for the poor foundation. Therefore, it is essential to ensure that students' emotions and responsibilities are appropriately controlled in order to ensure ongoing growth in...
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ISBN:
(纸本)9798350393415
Students are excellent at making make up for the poor foundation. Therefore, it is essential to ensure that students' emotions and responsibilities are appropriately controlled in order to ensure ongoing growth in tutoring close to a chance for improvement. Experts in several fields, including layout, have recently praised opinion mining (OM) as the greatest application. Managing and treating understudy beliefs can be difficult, especially when it comes to bearing because of the wide range of phonetics that students use and the volume of data that is available. Attitude mining is becoming more and more motivated, but there are still difficulties. The unique capability of the proposed SASCM, which monitors the undergraduate sentiment analysis comment model, is its capacity to mine comments from students who don't include outline messages. In a similar vein, it could benefit the directors by enabling the enhancement of the Opinion Mining interaction as a whole and carrying out the ensuing assessment to reactivate more illuminating foundations. This way, they can concentrate on understanding them to avoid the disastrous consequences on process learning. This will allow the directors to avoid having to deal with the bad effects of the encounters. Two of the three different modules in the proposed paradigm are the information Mining unit and the Data Preprocessing tool. Our essay's main goal is to change tutoring systems through an analysis of teacher, student, and instructor feedback. The proposed SASCM model uses a language-based approach to identify a method for removing a significant amount of information from each response in the data collection. It also uses a bundling efforts to create bundles for students using its remarks. The exploratory audit's findings suggested that a particular kind could examine student remarks. Numerous studies have been conducted into the organized model. By changing the layers of its units, the standard is far more adaptable than lectur
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