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In this paper, we compute the exact values of regularity of the quotient rings of the edge ideals associated to multi triangular snake and multi triangular ouroboros snake graphs. Also we compute the exact values of depth, Stanley depth, regularity and projective dimension of the quotient rings of the edge ideals associated to $q$-fold bristled graphs of multi triangular snake and multi triangular ouroboros snake graphs., Comment: Pages 18, figures 9

We obtain the exact values for depth and projective dimension and lower bounds for Stanley depth of the quotient rings of the edge ideals associated with all cubic circulant graphs., Comment: 20 pages, 7 figures

The tomato is one of the most important fruits on earth. It plays an important and useful role in the agricultural production of any country. This research propose a novel smart technique for early detection of late blight diseases in tomatoes. This work improve the dataset with an increase in images from the field (the Plant Village dataset) and proposed a hybrid algorithm composed of support vector machines (SVM) and histogram-oriented gradients (HOG) for real-time detection of late blight tomato disease. To propose a HOG-based SVM model for early detection of late blight tomato leaf disease. To check the performance of the proposed model in terms of MSE, accuracy, precision, and recall as compared to Decision Tree and KNN. The integration of advanced technology in agriculture has the potential to revolutionize the industry, making it more efficient, sustainable, and profitable. This research work on the early detection of tomato diseases contributes to the growing importance of smart farming, the need for climate-smart agriculture, the rising need to more efficiently utilize natural resources, and the demand for higher crop yields. The proposed hybrid algorithm of SVM and HOG has significant potential for the early detection of late blight disease in tomato plants. The performance of the proposed model against decision tree and KNN algorithms and the results may assist in selecting the best algorithm for future applications. The research work can help farmers make data-driven decisions to optimize crop yield and quality while also reducing the environmental impact of farming practices., Comment: The article titled "Early Detection of Late Blight Tomato Disease using Histogram Oriented Gradient based Support Vector Machine" need to be withdrawn there are other contributors in the improvement of this article

Web content should be accessible to normal and disabled communities on electronic devices. The Web Accessibility Initiative (WAI) has created standard guidelines called Web Content Accessibility Guidelines (WCAG). Mobile Web Best Practice (MWBP) is also proposed by WAI for accessibility of websites on desktop computers and mobile devices like smartphones, tablets, iPads, iPhones, and iPods. Educational Resources that provide free licensed learning content are used to test the WCAG. The disabled community also has equal rights to gain access to these learning materials through electronic devices. The main purpose of this research is to evaluate these selected open educational learning materials for individuals with only learning disabilities. This research provides several recommendations to improve the accessibility level of the Learning Management Systems. Future research includes developing a more accessible learning management system with minimized or no accessibility errors. Disability includes physical impairments, mental disorders, lack of cognition, learning and emotional disability. Some individuals have multiple disorders. Learning disabilities are one of them. People have difficulty learning because of an unknown factor or low intelligence quotient (IQ)., Comment: 15 pages

In order to predict and fill in the gaps in categorical datasets, this research looked into the use of machine learning algorithms. The emphasis was on ensemble models constructed using the Error Correction Output Codes framework, including models based on SVM and KNN as well as a hybrid classifier that combines models based on SVM, KNN,and MLP. Three diverse datasets, the CPU, Hypothyroid, and Breast Cancer datasets were employed to validate these algorithms. Results indicated that these machine learning techniques provided substantial performance in predicting and completing missing data, with the effectiveness varying based on the specific dataset and missing data pattern. Compared to solo models, ensemble models that made use of the ECOC framework significantly improved prediction accuracy and robustness. Deep learning for missing data imputation has obstacles despite these encouraging results, including the requirement for large amounts of labeled data and the possibility of overfitting. Subsequent research endeavors ought to evaluate the feasibility and efficacy of deep learning algorithms in the context of the imputation of missing data., Comment: 13 pages

We study the algebraic invariants namely depth, Stanley depth, regularity and projective dimension of the residue class rings of the edge ideals associated with the corona product of various classes of graphs with any graph. We also give an expression for the Krull dimension of the residue class rings of the edge ideals associated with the corona product of any two graphs. As a consequence, we characterize some Cohen-Macaulay graphs., Comment: 19 pages, 3 figures

Let $S$ be a ring of polynomials in finitely many variables over a field. In this paper we give lower bounds for depth and Stanley depth of modules of the type $S/I^t$ for $t\geq1$, where $I$ is the edge ideal of some caterpillar and lobster trees. These new bounds are much sharper than the existing bounds for the classes of ideals we considered., Comment: 17 pages, to appear in Mathematical Reports

Let S be a polynomial algebra over a field. If I is the edge ideal of a perfect semiregular tree, then we give precise formulas for values of depth, Stanley depth, projective dimension, regularity and Krull dimension of S/I., Comment: 17 pages, 4 figures