Multimodal learning analytics have become increasingly important in enabling a deeper understanding of teaching and learning in educational research. However, in comparison to other multimodal learning data, there is ...
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Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second ve...
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Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.
Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of featu...
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Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of features using typical *** a result,a new metaheuristicsbased feature selection method based on the dipper-throated and grey-wolf optimization(DTO-GW)algorithms has been developed in this *** can result when the selection of features is subject to metaheuristics,which can lead to a wide range of ***,we adopted hybrid optimization in our method of optimizing,which allowed us to better balance exploration and harvesting chores more *** propose utilizing the binary DTO-GW search approach we previously devised for selecting the optimal subset of *** the proposed method,the number of features selected is minimized,while classification accuracy is *** test the proposed method’s performance against eleven other state-of-theart approaches,eight datasets from the UCI repository were used,such as binary grey wolf search(bGWO),binary hybrid grey wolf,and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hysteresis optimization(bHy),and binary hysteresis optimization(bHWO).The suggested method is superior 4532 CMC,2023,vol.74,no.2 and successful in handling the problem of feature selection,according to the results of the experiments.
The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits freq...
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This article presents an experiment conducted among students of the Faculty of 'Software Engineering' of the Urgench branch of TATU named after Muhammad al-Khwarizmi. Teaching programming using online platform...
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Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comp...
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Morphological synthesis is a key aspect of natural language processing that focuses on the generation of word forms from their base components - roots, stems, prefixes, affixes, and inflectional morphemes. It plays a ...
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ISBN:
(数字)9798331516321
ISBN:
(纸本)9798331516338
Morphological synthesis is a key aspect of natural language processing that focuses on the generation of word forms from their base components - roots, stems, prefixes, affixes, and inflectional morphemes. It plays a crucial role in understanding and generating various grammatical forms of words in different languages. This process is essential for tasks such as machine translation, speech synthesis, text generation, and information retrieval. In agglutinative languages, words are formed by stringing together affixes that each represent a single grammatical function. Each morpheme retains its distinct meaning and function, making synthesis relatively predictable. In this article, using Kyrgyz as an example, we have examined the rules governing the attachment of affixes to words and assessed whether these affixes are correctly attached or if there are issues with morphological synthesis. This is, of course, a very topical issue. Because the first step in the problems of artificial intelligence is to pay attention to the features and ways of language creation.
The article proposes a method of zero-watermarking for colored RGB bitmap images. This algorithm can be used to protect property rights to multimedia resources in which it is impossible to use ordinary watermarks due ...
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ISBN:
(数字)9798350384499
ISBN:
(纸本)9798350384505
The article proposes a method of zero-watermarking for colored RGB bitmap images. This algorithm can be used to protect property rights to multimedia resources in which it is impossible to use ordinary watermarks due to the impossibility of changing the image (such as medical data where high accuracy is required and the appearance of artifacts is unacceptable) or due to the presence of a higher distortion of the container. This algorithm is based on DWT, SVD and operations in the field by modulo 256. The software implementation of the algorithm was developed (using the Accord and *** libraries to implement DWT, SVD). The software implementation of the algorithm was tested. This algorithm has advantages in the form of normalization of the average error, but it needs further research to improve its performance.
In this study, we present a straightforward teaching strategy for teaching the Python programming language. Our method emphasizes a clear progression from fundamental to sophisticated concepts. Beginning with a thorou...
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1 Introduction Traditional covert communication[1]usually relies on centralized channels,which are efficient in transmission but susceptible to eavesdropping and attacks,leading to information ***,distributed methods ...
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1 Introduction Traditional covert communication[1]usually relies on centralized channels,which are efficient in transmission but susceptible to eavesdropping and attacks,leading to information ***,distributed methods also exist,such as peer-to-peer networks and distributed hash *** technology,which is decentralized,anonymous,non-tamperable and anti-attack,can be applied to covert communication to solve the problems of traditional methods and improve the quality of communication.
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