scholarly journals On the Upper Bounds of Fractional Metric Dimension of Symmetric Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Muhammad Javaid ◽  
Muhammad Kamran Aslam ◽  
Jia-Bao Liu
Keyword(s):  
Image Processing ◽  
Drug Discovery ◽  
Computer Science ◽  
Chemical Compounds ◽  
Upper Bounds ◽  
Metric Dimension ◽  
Rotationally Symmetric ◽  
Metric Dimensions ◽  
Structural Aspects ◽  
Symmetric Networks

Distance-based numeric parameters play a pivotal role in studying the structural aspects of networks which include connectivity, accessibility, centrality, clustering modularity, complexity, vulnerability, and robustness. Several tools like these also help to resolve the issues faced by the different branches of computer science and chemistry, namely, navigation, image processing, biometry, drug discovery, and similarities in chemical compounds. For this purpose, in this article, we are considering a family of networks that exhibits rotationally symmetric behaviour known as circular ladders consisting of triangular, quadrangular, and pentagonal faced ladders. We evaluate their upper bounds of fractional metric dimensions of the aforementioned networks.

scholarly journals Classification of Upper Bound Sequences of Local Fractional Metric Dimension of Rotationally Symmetric Hexagonal Planar Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Shahbaz Ali ◽  
Muhammad Khalid Mahmood ◽  
Fairouz Tchier ◽  
F. M. O. Tawfiq
Keyword(s):  
Image Processing ◽  
Chemical Engineering ◽  
Chemical Compounds ◽  
Vital Role ◽  
Metric Dimension ◽  
Integer Programming Problem ◽  
Rotationally Symmetric ◽  
Metric Dimensions ◽  
Planar Networks

The term metric or distance of a graph plays a vital role in the study to check the structural properties of the networks such as complexity, modularity, centrality, accessibility, connectivity, robustness, clustering, and vulnerability. In particular, various metrics or distance-based dimensions of different kinds of networks are used to resolve the problems in different strata such as in security to find a suitable place for fixing sensors for security purposes. In the field of computer science, metric dimensions are most useful in aspects such as image processing, navigation, pattern recognition, and integer programming problem. Also, metric dimensions play a vital role in the field of chemical engineering, for example, the problem of drug discovery and the formation of different chemical compounds are resolved by means of some suitable metric dimension algorithm. In this paper, we take rotationally symmetric and hexagonal planar networks with all possible faces. We find the sequences of the local fractional metric dimensions of proposed rotationally symmetric and planar networks. Also, we discuss the boundedness of sequences of local fractional metric dimensions. Moreover, we summarize the sequences of local fractional metric dimension by means of their graphs.

scholarly journals Lower and Upper Bounds of Fractional Metric Dimension of Connected Networks

2021 ◽  
Vol 5 (4) ◽  
pp. 276
Author(s):  
Muhammad Javaid ◽  
Muhammad Kamran Aslam ◽  
Muhammad Imran Asjad ◽  
Bander N. Almutairi ◽  
Mustafa Inc ◽  
...  
Keyword(s):  
Large Scale ◽  
Chemical Compounds ◽  
Vital Role ◽  
Molecular Networks ◽  
Metric Dimension ◽  
Weighted Version ◽  
Shortest Distance ◽  
Metric Dimensions ◽  
Large Scale Networks ◽  
2D And 3D

The distance centric parameter in the theory of networks called by metric dimension plays a vital role in encountering the distance-related problems for the monitoring of the large-scale networks in the various fields of chemistry and computer science such as navigation, image processing, pattern recognition, integer programming, optimal transportation models and drugs discovery. In particular, it is used to find the locations of robots with respect to shortest distance among the destinations, minimum consumption of time, lesser number of the utilized nodes, and to characterize the chemical compounds, having unique presentations in molecular networks. After the arrival of its weighted version, known as fractional metric dimension, the rectification of distance-related problems in the aforementioned fields has revived to a great extent. In this article, we compute fractional as well as local fractional metric dimensions of web-related networks called by subdivided QCL, 2-faced web, 3-faced web, and antiprism web networks. Moreover, we analyse their final results using 2D and 3D plots.

scholarly journals Boundedness of Convex Polytopes Networks via Local Fractional Metric Dimension

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Muhammad Javaid ◽  
Hassan Zafar ◽  
Amer Aljaedi ◽  
Abdulaziz Mohammad Alanazi
Keyword(s):  
Convex Polytopes ◽  
Chemical Properties ◽  
Chemical Compounds ◽  
Molecular Networks ◽  
Metric Dimension ◽  
Optimal Solutions ◽  
Weighted Version ◽  
Shortest Distance ◽  
Metric Dimensions ◽  
And Chemical Properties

Metric dimension is one of the distance-based parameter which is frequently used to study the structural and chemical properties of the different networks in the various fields of computer science and chemistry such as image processing, pattern recognition, navigation, integer programming, optimal transportation models, and drugs discovery. In particular, it is used to find the locations of robots with respect to shortest distance among the destinations, minimum consumption of time, and lesser number of the utilized nodes and to characterize the chemical compounds having unique presentation in molecular networks. The fractional metric dimension being a latest developed weighted version of the metric dimension is used in the distance-related problems of the aforementioned fields to find their nonintegral optimal solutions. In this paper, we have formulated the local resolving neighborhoods with their cardinalities for all the edges of the convex polytopes networks to compute their local fractional metric dimensions in the form of exact values and sharp bounds. Moreover, the boundedness of all the obtained results is also proved.

Secondary Metabolites of Plant Origin containing Carbazole as Lead Molecule: A Review

2019 ◽  
Vol 05 ◽  
Author(s):  
Atul Sharma ◽  
Devender Pathak
Keyword(s):  
Drug Discovery ◽  
Heterocyclic Compounds ◽  
Biological Activities ◽  
Chemical Compounds ◽  
Lethal Effect ◽  
Chemical Diversity ◽  
Chemical Transformations ◽  
Pharmacological Effects ◽  
Structural Class ◽  
Biological Targets

Keeping this fact that study of a body is biology but life is all about chemicals and chemical transformations, many medicinal chemist start research in finding new and novel chemical compounds which having pharmacological activities. Most of those chemical compounds which are having active pharmacological effects are heterocyclic compounds. Heterocyclic compounds clutch a particular place among pharmaceutically active natural and synthetic compounds. The ability to serve both as biomimetics and reactive pharmacophores of heterocyclic nuclei is incredible and it has principally contributed to their unique value as traditional key elements of numerous drugs. These heterocyclic nuclei offer a huge area for new lead molecules for drug discovery and for generation of activity relationships with biological targets to enhance pharmacological effects. For these reasons, it is not surprising that this structural class has received special attention in drug discovery. The hydrogen bond acceptors and donors arranged in a manner of a semi-rigid skeleton in heterocyclic rings and therefore they can present a varied display of significant pharmacophores. Lead identification and optimization of drug target probable can be achieved by generation of chemical diversity produced by derivatization of heterocyclic pharmacophores with different groups or substituents. A tricyclic carbazole nucleus is an integral part of naturally occurring alkaloids and synthetic derivatives, possessing various potential biological activities such as anticancer, antimicrobial and antiviral. Binding mechanism of carbazole with target receptor as a molecule or fused molecule exhibits the potential lethal effect.

scholarly journals Bounds of Fractional Metric Dimension and Applications with Grid-Related Networks

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1383
Author(s):  
Ali H. Alkhaldi ◽  
Muhammad Kamran Aslam ◽  
Muhammad Javaid ◽  
Abdulaziz Mohammed Alanazi
Keyword(s):  
Metric Dimension ◽  
Hard Problem ◽  
Np Hard ◽  
Weighted Version ◽  
Sharp Bounds ◽  
Np Hard Problem ◽  
Metric Dimensions

Metric dimension of networks is a distance based parameter that is used to rectify the distance related problems in robotics, navigation and chemical strata. The fractional metric dimension is the latest developed weighted version of metric dimension and a generalization of the concept of local fractional metric dimension. Computing the fractional metric dimension for all the connected networks is an NP-hard problem. In this note, we find the sharp bounds of the fractional metric dimensions of all the connected networks under certain conditions. Moreover, we have calculated the fractional metric dimension of grid-like networks, called triangular and polaroid grids, with the aid of the aforementioned criteria. Moreover, we analyse the bounded and unboundedness of the fractional metric dimensions of the aforesaid networks with the help of 2D as well as 3D plots.

scholarly journals ChemBioServer 2.0: an advanced web server for filtering, clustering and networking of chemical compounds facilitating both drug discovery and repurposing

2020 ◽  
Vol 36 (8) ◽  
pp. 2602-2604 ◽  
Author(s):  
Evangelos Karatzas ◽  
Juan Eiros Zamora ◽  
Emmanouil Athanasiadis ◽  
Dimitris Dellis ◽  
Zoe Cournia ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Perfect Match ◽  
Web Server ◽  
Drug Repurposing ◽  
Chemical Compounds ◽  
Structural Similarity ◽  
Substructure Search ◽  
Similarity Network ◽  
Compound Libraries ◽  
Network Analysis Metrics

Abstract Summary ChemBioServer 2.0 is the advanced sequel of a web server for filtering, clustering and networking of chemical compound libraries facilitating both drug discovery and repurposing. It provides researchers the ability to (i) browse and visualize compounds along with their physicochemical and toxicity properties, (ii) perform property-based filtering of compounds, (iii) explore compound libraries for lead optimization based on perfect match substructure search, (iv) re-rank virtual screening results to achieve selectivity for a protein of interest against different protein members of the same family, selecting only those compounds that score high for the protein of interest, (v) perform clustering among the compounds based on their physicochemical properties providing representative compounds for each cluster, (vi) construct and visualize a structural similarity network of compounds providing a set of network analysis metrics, (vii) combine a given set of compounds with a reference set of compounds into a single structural similarity network providing the opportunity to infer drug repurposing due to transitivity, (viii) remove compounds from a network based on their similarity with unwanted substances (e.g. failed drugs) and (ix) build custom compound mining pipelines. Availability and implementation http://chembioserver.vi-seem.eu.

scholarly journals Dimensi Metrik Kuat Lokal Graf Hasil Operasi Kali Kartesian

2020 ◽  
Vol 1 (2) ◽  
pp. 64
Author(s):  
Nurma Ariska Sutardji ◽  
Liliek Susilowati ◽  
Utami Dyah Purwati
Keyword(s):  
Graph Theory ◽  
Cartesian Product ◽  
Metric Dimension ◽  
Star Graph ◽  
Product Graph ◽  
Path Graph ◽  
Strong Metric Dimension ◽  
Metric Dimensions ◽  
Development Result ◽  
Corona Product

The strong local metric dimension is the development result of a strong metric dimension study, one of the study topics in graph theory. Some of graphs that have been discovered about strong local metric dimension are path graph, star graph, complete graph, cycle graphs, and the result corona product graph. In the previous study have been built about strong local metric dimensions of corona product graph. The purpose of this research is to determine the strong local metric dimension of cartesian product graph between any connected graph G and H, denoted by dimsl (G x H). In this research, local metric dimension of G x H is influenced by local strong metric dimension of graph G and local strong metric dimension of graph H. Graph G and graph H has at least two order.

scholarly journals Analysis of Potholes on Road Using Image Processing

2021 ◽  
Vol 9 (8) ◽  
pp. 1731-1734
Author(s):  
K. S. Prasath
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Computer Science ◽  
Research Area ◽  
Raspberry Pi ◽  
Image Detection ◽  
The Road ◽  
Text Signals ◽  
Science Disciplines

Abstract: Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Nowadays, image processing is one among rapidly growing technologies. It forms core research area within engineering and computer science disciplines too. Image detection on road is primarily carried out with the help of camera with Raspberry pi 3 model b+ and stimulation software. The device is built in such a way that we can identify any potholes in the respective roads and able to rectify as soon as possible with the help of the device. The data signals shared by the device will be converted to text signals from which we can get it right. These devices are fixed at top of the lamppost which is located at the corners of the road from where the device is monitoring the road at 120 degree for weekly once respectively. Keywords: Image processing, Image detection on road, Raspberry pi 3, 120 degree

scholarly journals On distances in Sierpiński graphs: Almost-extreme vertices and metric dimension

2013 ◽  
Vol 7 (1) ◽  
pp. 72-82 ◽  
Author(s):  
Sandi Klavzar ◽  
Sara Zemljic
Keyword(s):  
Computer Science ◽  
Metric Dimension ◽  
Fractal Nature ◽  
Explicit Formulas ◽  
Arbitrary Vertex ◽  
Tower Of Hanoi ◽  
Sierpiński Graphs ◽  
Total Distance

Sierpi?ski graphs Sn p form an extensively studied family of graphs of fractal nature applicable in topology, mathematics of the Tower of Hanoi, computer science, and elsewhere. An almost-extreme vertex of Sn p is introduced as a vertex that is either adjacent to an extreme vertex of Sn p or is incident to an edge between two subgraphs of Sn p isomorphic to Snp-1. Explicit formulas are given for the distance in Sn p between an arbitrary vertex and an almostextreme vertex. The formulas are applied to compute the total distance of almost-extreme vertices and to obtain the metric dimension of Sierpi?ski graphs.

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