Emotion recognition is an increasingly relevant field due to its direct implications for various sectors of society. The area aims to enhance the understanding of how emotions influence human behavior. Exploring brain...
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Through this pandemic, the world has experienced two major crises, health crisis, and economic crisis. It would be dangerous for us to continue with our "normal"daily lives. We have been forced to stay at ho...
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Currently, in the process of assessing and giving feedback on students' argumentative writing, educators have to spend a considerable amount of time reading and analyzing each essay individually. This can be a com...
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Currently, in the process of assessing and giving feedback on students' argumentative writing, educators have to spend a considerable amount of time reading and analyzing each essay individually. This can be a complicated and time-consuming process, especially if the number of students to be assessed is quite large. The problem of this research is to find the most effective algorithm in providing accurate and reliable predictions in the context of evaluation and feedback of students' argumentation. This study compares three algorithms (logistic regression, Naive Bayes, and Random Forest) to predict student argumentation using essays from grades 6-12. Logistic regression performed best with 94.34% accuracy, followed by random forest with 91.98% accuracy, and Naive Bayes with 88.93% accuracy. The study optimized preprocessing and selected algorithms for an automated guidance model. It is the first stage of a three-part study for developing automated guidance models. Data came from Kaggle, and the study aims to improve the accuracy of automated guidance models for student argumentation.
We present a high-accuracy 3D facial reconstruction system with the following features: real-time 3D facial reconstruction using exposure synchronization multi-camera, feature alignment to quantify facial differences,...
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NoSQL database has gained popularity in Big Data and other various applications for its simplicity and flexibility. The non-relational nature of NoSQL database such as MongoDB proves to improve development lifecycles ...
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ISBN:
(数字)9798331542313
ISBN:
(纸本)9798331542320
NoSQL database has gained popularity in Big Data and other various applications for its simplicity and flexibility. The non-relational nature of NoSQL database such as MongoDB proves to improve development lifecycles and resources efficiency. However, security challenges arise along with increasing usage of NoSQL database, and NoSQL database is no exception to injection attacks. Machine learning proved to be an efficient method, as much has been researched. However, in the future there may be an increasing complexity of features that may prove costly to the model’s performance. Therefore, this research aims to utilize principal component analysis as dimensionality reduction and deep neural network as the classification method, to improve the security of NoSQL database. The text query is converted to feature vectors then further processed to reduce the input dimension of the deep neural network using PCA. The features used are based on previous research and various sources, and some are added after analyzing the dataset.10-fold cross validation is also applied to ensure that the model does not overfit the data, attempting to reduce bias to the result. The 10-fold cross validation model accuracy result is in average 97.44% with a standard deviation of 1.7%, and the testing results are 97.5% in accuracy,95.65% in precision, 91.67% in recall, and 93.61% in F1 score. Thus, it can be concluded that the usage of PCA on injection feature vectors can reduce complexity of the model.
作者:
Bakr, Hend A.Salama, Ahmed M.Fares, AhmedZaky, Ahmed B.Cairo University
Biomedical Engineering Program Faculty of Engineering Giza Egypt Benha University
Computer Systems Engineering Program Faculty of Engineering at Shoubra Banha Egypt
Computer science and information technology Programs Alexandria Egypt Benha University
On leave from Computer Systems Engineering Program Faculty of Engineering at Shoubra Egypt
Physician scheduling is a critical task that impacts the quality of patient care, staff satisfaction, and operational efficiency in healthcare institutions. The traditional approach to physician scheduling is manual a...
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Human-human interaction recognition is crucial in computer vision fields like surveillance,human-computer interaction,and social *** enhances systems’ability to interpret and respond to human behavior *** research fo...
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Human-human interaction recognition is crucial in computer vision fields like surveillance,human-computer interaction,and social *** enhances systems’ability to interpret and respond to human behavior *** research focuses on recognizing human interaction behaviors using a static image,which is challenging due to the complexity of diverse *** overall purpose of this study is to develop a robust and accurate system for human interaction *** research presents a novel image-based human interaction recognition method using a Hidden Markov Model(HMM).The technique employs hue,saturation,and intensity(HSI)color transformation to enhance colors in video frames,making them more vibrant and visually appealing,especially in low-contrast or washed-out *** filters reduce noise and smooth imperfections followed by silhouette extraction using a statistical *** extraction uses the features from Accelerated Segment Test(FAST),Oriented FAST,and Rotated BRIEF(ORB)*** application of Quadratic Discriminant Analysis(QDA)for feature fusion and discrimination enables high-dimensional data to be effectively analyzed,thus further enhancing the classification *** ensures that the final features loaded into the HMM classifier accurately represent the relevant human *** impressive accuracy rates of 93%and 94.6%achieved in the BIT-Interaction and UT-Interaction datasets respectively,highlight the success and reliability of the proposed *** proposed approach addresses challenges in various domains by focusing on frame improvement,silhouette and feature extraction,feature fusion,and HMM *** enhances data quality,accuracy,adaptability,reliability,and reduction of errors.
In this paper, we propose a novel Prior-Guided Parallel Residual Bi-Fusion Feature Pyramid Network (PPRB-FPN) for accurate obstacle detection in unmanned surface vehicle (USV) sailing. Our method tackles the challenge...
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Pupillometry measures pupil size, and several open-source algorithms are available to analyse pupillometry data. However, only a few studies compared these algorithms’ accuracy and computational resources. This study...
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Air pollution is a pressing issue in cities, and managing air quality poses a challenge for urban designers and decision-makers. This study proposes a Digital Twin (DT) Smart City integrated with Mixed Reality technol...
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