APAV - Academy of Sciences, Letters, Arts and Technology (E-Journals)
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The Outer Connected Detour Monophonic Number of a Graph
Full text linkFor a connected graph ???? = (????, ????) of order a set is called a monophonic set of ????if every vertex of ????is contained in a monophonic path joining some pair of vertices in ????. The monophonic number (????) of is the minimum cardinality of its monophonic sets. If or the subgraph is connected, then a detour monophonic set of a connected graph is said to be an outer connected detour monophonic setof .The outer connecteddetourmonophonic number of , indicated by the symbol , is the minimum cardinality of an outer connected detour monophonic set of . The outer connected detour monophonic number of some standard graphs are determined. It is shown that for positive integers , and ???? ≥ 2 with ,there exists a connected graph ????with???????????????????? = , ????????????m???????? = and = ????. Also, it is shown that for every pair of integers ????and b with 2 ≤ ???? ≤ ????, there exists a connected graph with and
The Edge-To-Vertex Triangle Free Detor Distance in Graphs
Full text linkFor every connected graph G, the triangle free detour distance D∆f(u, v) is the length of a longest u- v triangle free path in G, where u, v are the vertices of G. A u-v triangle free path of length D∆f(u, v) is called the u-v triangle free detour. In this article, the edge-to-vertex triangle free detour distance is introduced. It is found that the edge -to-vertex triangle free detour distance differs from the edge -to-vertex distance and edge-to-vertex detour distance. The edge-to-vertex triangle free detour distance is found for some standard graphs. Their bounds are determined and their sharpness is checked. Certain general properties satisfied by them are studied
Steiner domination decomposition number of graphs
Full text linkIn this paper, we introduce a new concept Steiner domination decomposition number of graphs. Let be a connected graph with Steiner domination numberA decomposition of is said to be a Steiner Domination Decomposition if Steiner domination decomposition number of is the maximum cardinality obtained for an of and is denoted as Bounds on are presented. Also, few characteristics of the subgraphs belonging to of maximum cardinality are discusse
White Hole existence on the inverse universe
Full text linkThe existence of White Hole (WH) has been suggested by Schwarzschild solution to the Einstein field equation as a time-reversed Black Hole (BH), besides there has not been observational evidence for their existence yet. Our idea of the “inverse universe”, in which we introduce the time-reversed kinematics as another geometric state, can explain that WH should appear in such a geometry after a matter falls into a BH. In this work, we present a new operation for WH conversion from BH, and by using it the nearly infinity point on the universe, for instance the inside of BH, is geometrically connected to the inside of WH on the inverse universe. Such a conversion is useful to provide the simple solution to the problem of “information loss” in BH. Furthermore, we find another conversion point as the prior geometric state to the Big Bang, and we propose a new cosmology of cyclic universe
Existence and Uniqueness of solution of Volterra Integrodifferential Equation of Fractional Order via S-Iteration
Full text linkIn this paper, we study the existence and other properties of solutions of existence and uniqueness of solution of Volterra integrodifferential equation of fractional order involving the Caputo fractional derivative. The tool employed in the analysis is based on application of iteration method. Since the study of qualitative properties in general required differential and integral inequalities, but here iteration method itself has equally important contribution to study various properties such as dependence on initial data, closeness of solutions and dependence on parameters and functions involved therein. Am example in support of the all established results
An Efficient Block-based Image Compression And Quality-Wise Decompression Algorithm
Full text linkIn this paper, we propose a block-based lossy image compression algorithm that makes use of spatial redundancies of neighboring pixels in image data. Compression is achieved by replacing a block of pixels with their statistical mean. The algorithm helps in decompressing the image at different quality levels. Quality matrices constructed from the quantization table of the JPEG baseline algorithm are used to achieve different qualities of the reconstructed data. Experimental results show that the proposed method outperforms existing polynomial-based algorithms both in computation time and complexity
The authorship of the Principle of Inertia
Full text linkAccording to some currents of modern historiography, Galilei's propensity for circular motion would have led him to consider this and not rectilinear motion as “natural motion”; therefore the principle of inertia could not be fully attributed to Galileo, which he would never have formulated. The question of the authorship of the principle of inertia certainly weighs on both nationalistic elements and returns of antigaleleism, while the question of its not explicit formulation as a principle is due to ignorance of the type of organization that Galileo intended to give to the exposition of his physics. The author, after having hinted at possible prodromes of the principle of inertia and having reported the adverse opinions of illustrious historians of science (A. Koyré, I. B. Cohen, P. M. Duhem, P. Rossi, G. Holton), through a careful analysis of the Galilean writings, conducted on the digital versions with the help of text analysis programs, firmly reaffirms Galileo's authorship of the principle of inertia and the consequent principle of classical relativity
Various Product on Multi Fuzzy Graphs
Full text linkIn this paper, the definition of complement of multi fuzzy graph, direct sum of two multi fuzzy graphs are given and derived some theorems related to them. Also, we examine the different product on multi fuzzy graphs such as Direct product, Cartesian product, Strong product, Composition, Corona product and some properties are analyze
A Deep Learning Model for Classifying the Hate and Offensive Language in Social Media Text
Full text linkRecently, we had introduced a model for identifying and removal of toxic content from twitter, using an Information Retrieval (IR) model SOIR (Semantic query Optimization-based Information Retrieval). Based on lexical and semantic analysis, SOIR identifies the class labels of tweets. The result demonstrates the superiority of the SOIR model. This model is accurate but social media is a big data problem and a significant amount of time and memory is required. In this paper the deep learning technique is used to process large-scale social media text data. First uses Natural Language Processing (NLP) based feature extraction to create four different sets of training samples i.e. TF-IDF-based features, POS Tagged Features, a reduced feature vector of POS and the combined vector of TF-IDF and POS tagged features. The deep Convolutional Neural Networks (CNN) is used to train the model and to classify hate and offensive language. The dataset has been obtained from Kaggle. The performance in terms of training accuracy, validation accuracy, training loss and validation loss has been measured with the time complexity. In addition, the class-wise Precision, Recall, F1-score, and Mean accuracy have also been investigated. From experimental results, we found TF-IDF and POS-based combined features provide superior performance
An Adaptive Neural Network Approach To Predict The Capital Adequacy Ratio
Full text linkFinancial institutions, policy makers and regulatory authorities need to implement stress tests in order to test both resilience and the consequences of adverse shocks. The European Central Bank and the European Banking Authority regularly conduct these tests, whose importance is more and more evident after the financial crisis of 2007-2008. The stress tests’ nonlinear features of variables and scenarios triggered the need of general and robust strategies to perform this task. In this paper we want to introduce an adaptive Neural Network approach to predict the Capital Adequacy Ratio (CAR), which is one of the main ratios monitored to retrieve useful information along many stress test procedures. The Neural Network approach is based on a comparison between feed-forward and recurrent networks, and is run after a meaningful pre-processing operations definition. Results show that our approach is able to successfully predict CAR by using both Neural Networks and recurrent networks