In recent years, Artificial Intelligence (AI) has gained increasing popularity in the area of art creation, by demonstrating its great potential. Research in this topic has developed AI systems able to generate creati...
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Credit card theft is on the upswing as technology advances. Also, it may be appealing that as global communication advances, economic fraud is sharply rising. Millions of dollars are lost every day due to these frauds...
Credit card theft is on the upswing as technology advances. Also, it may be appealing that as global communication advances, economic fraud is sharply rising. Millions of dollars are lost every day due to these frauds, according to records. master card fraud states to the somatic forfeiture of the master card or defeat of profound master card information. For detection, a variety of machine learning methods are frequently utilized. This study presents a few of the algorithms that will be used to catalogue connections as faithful or fraudulent credit cards. The study used a dataset for fraud detection. Sorting and searching were utilized for oversampling because the dataset was quite unbalanced. NFC technology is decisive for user re-authentication as integrates the Internet of Things for double transaction verification to reduce fraudulent transactions, Random Forest, Bayesian Network, and Multilayer Perception were the strategies adopted in the experiment, including feature selection and dataset division into training and test data. Results show that every technique is regularly and reliably used to spot master card fraud.
Requirements traceability remains a challenge, especially in multi-level system of systems being developed by many different organizations. This paper develops and tests automated tracing methods based on Natural Lang...
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In this paper, we classify Gram positive cocci and Gram negative bacilli in Gram stained smear images. We adopt pre-trained models of VGG16, VGG19, MobileNet and DenseNet by using ImageNet as learning models. Then, we...
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correct understanding of the Holy Quran is an essential duty for all Muslims. Tajweed rules guide the reciter to perform Holy Quran reading exactly as it was uttered by Prophet Muhammad peace be upon him. This work fo...
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correct understanding of the Holy Quran is an essential duty for all Muslims. Tajweed rules guide the reciter to perform Holy Quran reading exactly as it was uttered by Prophet Muhammad peace be upon him. This work focused on the recognition of one Quranic recitation rule. Qalqalah rule is applied to five letters of the Arabic Alphabet (Baa/Daal/Jeem/Qaaf/Taa) having sukun vowelization. The proposed system used the Mel Frequency Cepstral Coefficients (MFCC) as the feature extraction technique, and the Convolutional Neural Networks (CNN) model was used for recognition. The available dataset consists of 3322 audio samples from different surahs of the Quran for four professional readers (Sheihk) AlHussary, AlMinshawy, Abdel Baset, and Ayman Swayed. The best results were gained using Ayman Swayed audio samples with a validation accuracy of 90.8%.
To index the increasing volume of data, modern data indexes are typically stored on SSDs and cached in DRAM. However, searching such an index has resulted in significant I/O traffic due to limited access locality and ...
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In recent years, women’s reproductive health has become a significant concern. Issues like preterm abortions, infertility, ovarian disorders, and declining fertility rates are prevalent. Polycystic Ovarian Syndrome (...
In recent years, women’s reproductive health has become a significant concern. Issues like preterm abortions, infertility, ovarian disorders, and declining fertility rates are prevalent. Polycystic Ovarian Syndrome (PCOS), a common reproductive disorder, often leads to infertility due to irregular cycles and elevated androgens. Despite its unclear cause and cure, early detection and intervention are vital. Researchers are exploring AI-based diagnostics to expedite diagnosis and mitigate clinical challenges. Our methodology revolves around leveraging non-invasive parameters to construct a feature vector optimized for machine learning algorithms. We utilize Principal Component Analysis (PCA) as a crucial step for dimensionality reduction, which streamlines the dataset’s representation while retaining vital information. To bolster the accuracy of PCOS diagnosis, we deploy a majority voting ensemble model that incorporates five base models. This ensemble approach not only enhances classification precision but also addresses issues like overfitting and model robustness, making it especially valuable when dealing with datasets of limited size. The accuracy, precision, f1-score, and recall for the suggested model are found to be 84.3%, 76.1%, 81%, and 84.3% respectively. Our research shows that our ensemble model performs better overall and across individual classes than the fundamental models. This development represents a substantial advancement in the field of PCOS diagnosis, showcasing the pivotal role of machine learning in enhancing diagnostic precision.
Path planning improves the performance and robustness of vision-based robot control in unstructured environments. Visual servo path planning usually focuses only on the path of the camera in the Cartesian space or the...
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In this paper, the strong stabilization of the Acrobot at the Down-Up equilibrium point is addressed, with the first link being downward and the second link being upright. By converting the strong stabilization of the...
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In this paper, the strong stabilization of the Acrobot at the Down-Up equilibrium point is addressed, with the first link being downward and the second link being upright. By converting the strong stabilization of the Acrobot at the Down–Up equilibrium point equivalently to the existence and design of a stable stabilizing controller for a fourth-order single-input single-output linear plant with adjustable zeros, a pair of poles on the imaginary axis, and a pair of real poles located symmetrically with respect to the origin, this paper has three main contributions. Firstly, the existence of a stable stabilizing controller for any Acrobot which is linearly controllable at the Down–Up equilibrium point is proved by showing the range of the adjustable zero via adjusting a parameter of the output signal. Secondly, a necessary and sufficient condition on the mechanical parameters of the Acrobot is provided to guarantee the existence of a second-order stable stabilizing controller for the Acrobot around its Down– Up equilibrium point. Thirdly, a direct method is presented to design a second-order stable controller, whose transfer function is preset with three parameters. By utilizing the Liénard– Chipart criterion for a fourth-order polynomial, the necessary and sufficient conditions on these parameters for achieving the strong stabilization are obtained, which are expressed in a cascade form for obtaining these parameters conveniently. A numerical example is presented to validate the effectiveness of the proposed method.
Nowadays screen-shooting resilient watermarking still remains as a predictive and challenging area of research for proactive data protection in consumer electronic applications. Present deep learning-based methodologi...
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