A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,w...
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A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.
Symmetric algorithms offer speed but have weaknesses in key distribution, while asymmetric algorithms are secure but less efficient for encrypting and decrypting large text messages. This research aims to secure data ...
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ISBN:
(数字)9798331531249
ISBN:
(纸本)9798331531256
Symmetric algorithms offer speed but have weaknesses in key distribution, while asymmetric algorithms are secure but less efficient for encrypting and decrypting large text messages. This research aims to secure data and digital documents through the implementation of a hybrid cryptosystem that combines the Cramer-Shoup algorithm and Spritz. This research also analyzes and evaluates the effectiveness and speed of encryption and decryption, as well as the efficiency of the system in protecting various types of data, including docx and pdf document files. The methodology of this research includes a literature review, analysis of the encryption-decryption process, and performance testing of the system using the Python programming language. The speed test results show that this hybrid cryptosystem provides fast encryption-decryption times, with an encryption time of 0.002607 milliseconds for 400 characters and a decryption time of 0.001537 milliseconds, while for digital documents of the pdf file type, the encryption time is 0.424478 milliseconds and the decryption time is 0.404343 milliseconds. In addition, the use of the SHA-3 hash function has proven effective in maintaining data integrity. In conclusion, this hybrid cryptosystem offers an efficient and secure solution for protecting various types of digital data, including text and documents.
In an attempt to bridge the semantic gap between language understanding and visuals, Visual Question Answering (VQA) offers a challenging intersection of computer vision and natural language processing. Large Language...
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ISBN:
(数字)9798350362633
ISBN:
(纸本)9798350362640
In an attempt to bridge the semantic gap between language understanding and visuals, Visual Question Answering (VQA) offers a challenging intersection of computer vision and natural language processing. Large Language Models (LLMs) have shown remarkable ability in natural language understanding; however, their use in VQA, particularly for Arabic, is still largely unexplored. This study aims to bridge this gap by examining how well LLMs can improve VQA models. We use state-of-the-art AI algorithms on datasets from multiple fields, including electric devices, Visual Genome, RSVQA, and ChartsQA. We introduce ArabicQuest, a Text Question Answering (TQA) tool that combines Arabic inquiries with visual data. We assess the performance of LLMs across various question types and image settings and find that fine-tuning me thods su ch as LLaMA-2, BLIP-2, and Idefics-9B-Instruct models provide encouraging results, although challenges still arise in counting and comparison tasks. Our findings demonstrate the importance of advancing VQA further—especially for Arabic—to enhance accessibility and user satisfaction in a variety of applications.
Online discussion forums are widely used for active textual interaction between lecturers and students, and to see how the students have progressed in a learning process. The objective of this study is to compare appr...
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In this article, we propose to study a novel research problem to boost group performance, that is, social-aware diversity-optimized group extraction (SDGE), which takes into consideration the two important factors: 1)...
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This study develops an adaptive handover strategy in 5G networks to tackle high mobility challenges and improve service continuity and quality. The research method uses a 5G network emulator with a topology of four ba...
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Several challenges have emerged as a result of the rapid spread of Covid-19 in Indonesia. To combat the pandemic, the government has also issued general guidelines for avoiding/limiting direct contact with common peop...
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The use of technology nowadays does not feel strange. Everyday people who use technology for their daily needs, starting with each other, seeking knowledge, can even earn income by doing business using technology. Soc...
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Infertile patients may be a high-risk group of mental disorder. The precise identification of the mental status of infertile patients can provide decision support to healthcare professionals and may be helpful in prov...
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computer vision has emerged as an important subject of study, with several practical applications in a wide range of domains. OpenCV, a widely used framework, has played an important role in allowing computer vision t...
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