Applications utilizing the Internet of Things (IoT) operate on a platform that works efficiently and has capabilities of handling vast volumes of data processing. The type of application will determine if this platfor...
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A large-scale electric vehicles (EVs) integration will result in different load profiles depending on the charging strategy being used. Consequently, this will have an impact on the dynamic behavior of the power syste...
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Landslides inflict substantial societal and economic damage, underscoring their global significance as recurrent and destructive natural disasters. Recent landslides in northern parts of India and Nepal have caused si...
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In the domain of bioinformatics, DNA sequence classification is an indispensable tool that spans various scientific disciplines, contributing to scientists' understanding of biology, aiding in the identification o...
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ISBN:
(纸本)9798350350289
In the domain of bioinformatics, DNA sequence classification is an indispensable tool that spans various scientific disciplines, contributing to scientists' understanding of biology, aiding in the identification of genes, regulatory elements, and the functional significance of distinct genomic regions. Moreover, it plays a vital role in disease diagnosis, treatment strategies, drug discovery, evolution, agriculture, forensic identification, environmental monitoring and more. The classification process involves the intricate mapping of DNA sequences to distinct classes based on the arrangement of nucleotides. A fractional mutation in the sequence corresponds to a nuanced shift in the assigned class. Every numerical instance, serving as a depiction of a particular class, is closely associated with a specific gene lineage. In this study, for the DNA sequence preprocessing, both K-mer counting and count vectorization were used respectively. Afterwards, we utilized a variety of classifier models, encompassing Multinomial naive bayes (MNB), Logistic regression (LR), Random forest (RF), LightGBM (LGMB), XGBoost (XGB), K-nearest neighbors (KNN) and Decision tree (DT) algorithm on three types of DNA sequence datasets (Human, Chimpanzee & Dog) to identify each of sequence's corresponding gene class (0, 1, 2, 3, 4, 5, & 6). Then, the highest three and highest five classifier models were picked based on their accuracy scores. Afterwards, both soft voting and hard voting ensemble methods were implemented on this cluster of fundamental models to effectively leverage their collective predictive strength. The soft voting ensemble on the best three models consistently reached the highest accuracy across all three datasets. Employing this ensemble method, the human, chimpanzee, and dog datasets exhibited highest performance metrics i.e. accuracy, precision, recall, and fl-scores of (98.42 %, 98.41 %, 98.40%, 98.40%), (92.28%, 92.40%, 92.30%, 92.10%), and (70.12%, 73.10%, 70.10%, 69.2
A content-based image retrieval system (CBIR) needs intensity/weighted importance for individual features of an image to find similar images in the database to achieve better results. Generally, these weights are assi...
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The integrity of product warranties stands as a critical concern, marked by challenges like data tampering and fabrication within traditional verification systems. This paper explores the transformative potential of b...
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In today's digital age, there is a grow in demand for unique and personalized artistic contents which paves a path for NFT marketplace. NFT marketplace is a platform for the sale and auction of the contents produc...
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This study presents a comprehensive intervention approach designed to address dyscalculia in early education. The strategy employs a comprehensive approach that incorporates colour identification, numerical enumeratio...
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Imagine numerous clients,each with personal data;individual inputs are severely corrupt,and a server only concerns the collective,statistically essential facets of this *** several data mining methods,privacy has beco...
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Imagine numerous clients,each with personal data;individual inputs are severely corrupt,and a server only concerns the collective,statistically essential facets of this *** several data mining methods,privacy has become highly *** a result,various privacy-preserving data analysis technologies have ***,we use the randomization process to reconstruct composite data attributes ***,we use privacy measures to estimate how much deception is required to guarantee *** are several viable privacy protections;however,determining which one is the best is still a work in *** paper discusses the difficulty of measuring privacy while also offering numerous random sampling procedures and statistical and categorized data ***-more,this paper investigates the use of arbitrary nature with perturbations in privacy *** to the research,arbitrary objects(most notably random matrices)have"predicted"frequency *** shows how to recover crucial information from a sample damaged by a random number using an arbi-trary lattice spectral selection *** system's conceptual frame-work posits,and extensive practicalfindings indicate that sparse data distortions preserve relatively modest privacy protection in various *** a result,the research framework is efficient and effective in maintaining data privacy and security.
Our project pioneers a transformative platform, marrying artificial intelligence with fashion customization. Users engage with an intuitive interface, seamlessly translating their style visions into unique apparel des...
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