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Restrained geodetic domination of edge subdivision graph
For a connected graph G = (V,E), a set S subset of V (G) is said to be a geodetic set if all vertices in G should lie in some u-v geodesic for some u,v S. The minimum cardinality of the geodetic set is the geodetic number. In this paper, the authors discussed the geodetic number, geodetic domination number, and the restrained geodetic domination of the edge subdivision graph. 2022 World Scientific Publishing Company. -
Restrained geodetic domination in graphs
Let G = (V,E) be a graph with edge set E and vertex set V. For a connected graph G, a vertex set S of G is said to be a geodetic set if every vertex in G lies in a shortest path between any pair of vertices in S. If the geodetic set S is dominating, then S is geodetic dominating set. A vertex set S of G is said to be a restrained geodetic dominating set if S is geodetic, dominating and the subgraph induced by V - S has no isolated vertex. The minimum cardinality of such set is called restrained geodetic domination (rgd) number. In this paper, rgd number of certain classes of graphs and 2-self-centered graphs was discussed. The restrained geodetic domination is discussed in graph operations such as Cartesian product and join of graphs. Restrained geodetic domination in corona product between a general connected graph and some classes of graphs is also discussed in this paper. 2020 World Scientific Publishing Company. -
Restrained geodetic domination in the power of a graph
For a graph G = (V,E), S ? V(G) is a restrained geodetic dominating set, if S is a geodetic dominating (gd) set and never consists an isolated vertex. The least cardinality of such a set is known as the restrained geodetic domination (rgd) number. The power of a graph G is denoted as Gk and is obtained from G by making adjacency between the vertices provided the distance between those vertices must be at most k. In this study, we discussed geodetic number and rgd number of Gk. 2024 Author(s). -
User Authentication with Graphical Passwords using Hybrid Images and Hash Function
As per human psychology, people remember visual objects more than texts. Although many user authentication mechanisms are based on text passwords, biometric characteristics, tokens, etc., image passwords have proven to be a substitute due to its ease of use and reliability. The technological advancements and evolutions in authentication mechanisms brought greater convenience but increased the probability of exposing passwords through various attacks like shoulder-surfing, dictionary, key-logger, and social engineering attacks. The proposed methodology addresses these vulnerabilities and ensures to keep up the usability of graphical passwords. The system displays hybrid images that users need to recognize and type the randomly generated alphanumeric or special character values associated with each of them. A mechanism to generate One Time Password (OTP) is included for additional security. As a result, it is difficult for an attacker to capture and misuse the password. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
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Cognitive Style and Academic Achievement among School Students
The aim of the present study was to explore cognitive style and academic achievement among school students using a quantitative approach. The study involved a total of 423 students from grade VIth and VIIth. Students from both private and government schools participated in the study. The study used group embedded figures test by Witkin et al. (1971) and classroom achievement test by Singh & Gupta (2007) to determine the participants field independent and dependent cognitive styles and academic achievement. T test was used to compare the academic achievement of field independent ?? field dependent cognitive style students. Whereas, two-way Anova test was done to analysis the interaction effect of grades, gender, and type of school along with cognitive style on academic achievement of students. The findings of the present research showed that there was a significant difference between field independent and dependent students' on academic achievement. It also revealed that students with field independent cognitive style performed significantly better than field dependent students. However grades had a significant main effect on academic achievement of students. There was no interaction effect found between grades and cognitive style on academic achievement of students. In addition, it was also found that there was no interaction effect of type of school and cognitive style on academic achievement of students. The findings of the study benefits teachers by indicating significant classroom implications which will help them to develop effective learning materials and strategies which are suitable for their student in order to utilize their cognitive style strength effectively. It helps students in making effective decisions regarding ones enrolment in higher education courses and career choices. Key Words: Field Independent-Dependent Cognitive Style, Academic Achievement, Grades, Gender and Type of School. -
Activity Classifier: A Novel Approach Using Naive Bayes Classification
Activity movements have been recognized in various applications for elderly needs, athletes activities measurements and various fields of real time environments. In this paper, a novel idea has been proposed for the classification of some of the day to day activities like walking, running, fall forward, fall backward etc. All the movements are captured using a Light Blue Bean device incorporated with a Bluetooth module and a tri-axial acceleration sensor. The acceleration sensor continuously reads the activities of a person and the Arduino is designed to continuously read the values of the sensor that works in collaboration with a mobile phone or computer. For the effective classification of a persons activity correctly, Nae Bayes Classifier is used. The entire Arduino along with acceleration sensor can be easily attached to the foot of a person right at the beginning of the user starts performing any activity. For the evaluation purpose, mainly four protocols are considered like walking, running, falling in the forward direction and falling in the backward direction. Initially five healthy adults were taken for the sample test. The results obtained are consistent in the various test cases and the device showed an overall accuracy of 90.67%. Springer Nature Switzerland AG 2020. -
Process scheduling in heterogeneous multicore system using agent based graph coloring algorithm
In any heterogeneous multicore system, there are numerous amount of processors with different platform and all the processing units are fabricated on a common single unit preferably on a System on Chip. As there is a tremendous amount of parallelism encompassed in a multicore system, proper utilization of the cores is a big challenge in the current era. Hence a more automated software approach is required like an agent based graph coloring algorithm to find the free processor and schedule the tasks on the respective cores. Predominantly the entire process of scheduling the tasks on multicore system is based on arrival time of process. This paper incorporates the scheduling on the linux 2.6.11 kernel and GEMS simulator for multicore implementation. The core utilization in this type of agent scheduling is 50% more than the existing scheduling mechanism. BEIESP. -
Captcha-Based Defense Mechanism to Prevent DoS Attacks
The denial of service (DoS) attack, in the current scenario, is more vulnerable to the banking system and online transactions. Conventional mechanism of DoS attacks consumes a lot of bandwidth, and there will always be performance degradation with respect to the traffic in any of the communication networks. As there is an advent over the network bandwidth, in the current era, DoS attacks have been moved from the network to servers and API. An idea has been proposed which is CAPTCHA-based defense, a purely system-based approach. In the normal case, the protection strategy for DDoS attacks can be achieved with the help of many session schedulers. The main advantage is to efficiently avoid the DoS attacks and increase the server speed as well as to avoid congestion and data loss. This is majorly concerned in a wired network to reduce the delays and to avoid congestion during attacks. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Multilevel Security and Dual OTP System for Online Transaction Against Attacks
In the current internet technology, most of the transactions to banking system are effective through online transaction. Predominantly all these e-transactions are done through e-commerce web sites with the help of credit/debit cards, net banking and lot of other payable apps. So, every online transaction is prone to vulnerable attacks by the fraudulent websites and intruders in the network. As there are many security measures incorporated against security vulnerabilities, network thieves are smart enough to retrieve the passwords and break other security mechanisms. At present situation of digital world, we need to design a secured online transaction system for banking using multilevel encryption of blowfish and AES algorithms incorporated with dual OTP technique. The performance of the proposed methodology is analyzed with respect to number of bytes encrypted per unit time and we conclude that the multilevel encryption provides better security system with faster encryption standards than the ones that are currently in use. 2019 IEEE. -
Social environment based on sentiments using globalized user review analysis /
Patent Number: 202141007727, Applicant: Dr.G Muneeswari.
A simple yet efficient model, called Globalized User Sentiment Analysis (GURA) by using the property that sentiment classification has two opposite class labels (i.e., positive and negative), we first propose a data expansion technique by creating sentiment toggled reviews. The original and switched reviews are constructed in a one-to-one correspondence. Thereafter, we enhance the dual training (DT) algorithm and a dual forecasting (DF) algorithm separately, to make use of the original and switched samples in pairs for training a statistical classifier and make predictions. -
Comparative Study on the Experimental Results on Low-Velocity Impact Characteristics of GLARE Laminates with Simulation Results from LS Dyna
Fiber reinforcement with metallic face sheets is one of the recently implemented materials for distinctive applications in automotive and aerospace sectors. While the reinforcement enhances the sustenance property of the laminate, the face sheets provide resistance to impact force. In most automotive sectors, drop weight analysis at varying velocity ranges is performed to evaluate the damage characteristics of the vehicle body. The present work is aimed at studying the influence of low-velocity impact (LVI) on Glass Laminate Aluminum-Reinforced Epoxy (GLARE) laminate. Three distinct thicknesses of Al-2024 T3 aluminum alloy (0.2, 0.3 and 0.4mm) were chosen as the face sheet and E-glass fiber was used as intermediate layers. Epoxy resin LY556 with a HY951 hardener was used to fabricate the GLARE structure and the overall thickness was maintained at 2.0mm for all the cases. Energy absorbed by GLARE laminates for different energy was determined using Drop weight Impact test experimentally and analytically. The laminate and the dart were modeled by ANSYS ACP tool and the simulation was performed using LS Dyna software. It was evident that laminate can sustain impact at a velocity of 3.13m/s and beyond which leads to surface delamination. The simulation results were in close agreement with the experimental values for the absorbed energy, with less than 10% error. 2022, The Institution of Engineers (India). -
Improving Renewable Energy Operations in Smart Grids through Machine Learning
This paper reviews the work in the areas of machine learning's role in bolstering renewable energy within smart grids. As the global shift towards eco-friendly energy sources such as wind and solar gains momentum, the challenge lies in managing these unpredictable energy sources efficiently. Innovative learning techniques are emerging as potential solutions to these challenges, optimising the use and benefits of renewable energies. Furthermore, the landscape of energy distribution is evolving, with a growing emphasis on automated decision-making software. Central to this evolution is machine learning, with its applications spanning a range of sectors. These include enhancing energy efficiency, seamlessly integrating green energy sources, making sense of vast data sets within smart grids, forecasting energy consumption patterns, and fortifying the security of power systems. Through a comprehensive review of these areas, this paper highlights the potential of machine learning in paving the way for a greener, more efficient energy future. The Authors, published by EDP Sciences, 2024. -
A Review on Condition Monitoring of Wind Turbines Using Machine Learning Techniques
This document examines the most up-to-date research on the application of machine learning (ML) techniques in monitoring the conditions of wind turbines. The focus is on classification methods, which are used to identify different types of faults. The analysis revealed that the majority of the research utilizes Supervisory Control and Data Acquisition (SCADA) information, with neural networks, support vector machines, and decision trees being the most prevalent machine learning algorithms. The review also identifies several areas for future research, such as the development of more robust ML models that can handle noisy data and the use of ML methods for prognosis (predicting future faults). The Authors, published by EDP Sciences, 2024. -
Future Perspectives of Microplastic towards Environmental Assessment
Microplastic (MP) pollution is an outcome of the widespread use of non-biodegradable plastic and improper disposal. This leads to contamination of environmental resources, such as landfills, and all kinds of water reservoirs including but not limited to sea, fresh water, drinking water, and even wastewater. Recent reports have highlighted the presence of MPs in the human body, including blood, lungs, placentas, and breast milk, indicating the severity of the issue. It is thus crucial to eliminate these hazardous contaminants from the environment. One of the effective methods to address the concern while reducing the adverse effects is to remove the MPs at their discharge points. Nanomaterials with exceptional properties like high surface area, ease of functionalization, and high affinity toward various pollutants act as excellent adsorbents. In this chapter, we present an overview of emerging nanomaterial-based adsorbents, such as photocatalysts, metal-organic frameworks, carbon-based nanomaterials, and nanocomposites, for effective removal of MPs from aqueous media via adsorption, photo-catalysis, and membrane filtration. However, considering that the research in the area of MP pollution is still in its infant stage, we aim to provide a brief account of the strengths, weaknesses, and future research dimensions of nanomaterial-based adsorbents for removing MPs from aqueous media. 2025 selection and editorial matter, Nirmala Kumari Jangid and Rekha Sharma; individual chapters, the contributors. -
Inkjet printing of MOx-based heterostructures for gas sensing and safety applicationsRecent trends, challenges, and future scope
Volatile organic compounds (VOCs) are pollutants that affect air quality and human health. Detection of VOCs is important for environmental safety. Metal oxide semiconductor (MOS) is a promising product for gas sensors due to its advantages of easy fabrication, low cost, and good portability. Their performance is greatly affected by microstructure, defects, catalysts, heterojunctions, and moisture. Metal oxidebased nanomaterials serve as a platform to identify various VOCs with high sensitivity due to their wide bandgap, n-type transport, and excellent electrical properties. Gas detection devices based on doping, altered morphology, and heterostructure have been shown to be effective against VOCs. Inkjet printing (IJP) is a promising process for the room-temperature deposition of functional metal oxides for sensing applications. However, the development of metal oxide ink requires a careful selection of the precursors, solvents, and additives. This section will focus on the production of various metal oxide (MOx)-based sensors such as ZnO, SnO2, MoO3, CuO, Cu2O, Mn3O4, and WO3 for the detection of VOCs such as acetylene, toluene, ethanol, formaldehyde, and acetone. It will summarize recent research and advances in large-scale printing of MOx-based nanocomposites. This work illustrates the need to explore new composite materials, structures, and morphology as well as other methods for better and faster transformation. The role of solvents in ink stabilization and printing and the behavior of ink rheological parameters in the IJP spraying process will also be discussed. Ink formulations for the synthesis of functional nanocomposites will be analyzed and presented for future scope and challenges. 2024 Elsevier Inc. All rights reserved. -
Graphitic carbon nitride (GCN) for solar cell applications
There is an eminent global energy crisis and photovoltaics as one of the primary renewable energy sources is playing an important part in offsetting the dependency on fossil fuels. Current solar cells technology is dominated by silicon, and researchers are trying to replace it with organic and nanocrystalline semiconducting materials. Graphitic carbon nitride (g-C3N4, GCN) has gained interest as a visible light driven photocatalyst with a unique 2D structure, excellent chemical stability and tunable electronic structure along with attractive optoelectronic properties. Pure GCN suffers from low surface area and rapid recombination of photo-generated electron-hole pairs resulting in low photovoltaic and photocatalytic activity and hence modification by doping with other atoms is required. Photocatalytic applications of GCN based nanomaterials for water splitting, hydrogen production, CO2 reduction and pollutant degradation has been extensively investigated and systematically reviewed. However, their applications as energy storage has been explored recently and there is a lack of comprehensive review that systematically summarizes the application of GCN and GCN-based heterostructures for solar cell applications. Heterojunctions with superior light absorption and appropriate conduction band and valence band alignment is a promising approach for the applications in efficient environmental remediation and solar energy storage. This critical review summarizes the synthesis and advances of GCN nanocomposites modified with semiconductors (TiO2, ZnO), bismuth titanate, strontium titanate and rare earth metals for solar cell applications. GCN-based heterostructures with perovskite and polymer based materials are also presented. The characteristics and transfer mechanism within the various heterojunctions is also reviewed and presented. The review ends with a summary and some perspectives on the challenges and new directions in exploring GCN-based advanced nanomaterials particularly towards photovoltaics and energy storage applications. 2022 Elsevier Inc. All rights reserved. -
Nanoarchitectures as photoanodes
This chapter looks into providing detailed information on the state-of-the-art and recent trends on materials and nanoarchitectures for improved photoanode device. It provides a roadmap for researchers toward optimization of photoanodes using advanced material engineering. The chapter casts some light on the performance of various photoanode materials and nanostructures, such as TiO2, ZnO, SnO2, Nb2O5, Al2O3, ZrO2, CeO2, SrTiO3, Zn2SnO4, and carbon in dye-sensitized solar cells (DSSCs). Plasmonic photoanodes are an emerging field in DSSC spanning a wide range of materials where the paramount challenge is coming up with effective strategies to incorporate suitable plasmonic structures into nanocrystalline and nanostructured electrodes. Optical excitation of the dye is the basis of DSSC operation, where an electron is excited from the dye molecule into the conduction band of a wideband metal oxide. 2020 JohnWiley & Sons Inc. All rights reserved. -
Novel Anti-Corrosion and Anti-Fouling Coatings and Thin Films
Nanomaterials and nanocomposite materials have been developed as corrosion inhibitors and are the most noble and effective alternatives to traditional organic corrosion inhibitors. Nanomaterials provide reasonably high anticorrosive activity in both aqueous and solution phases. A unified approach to this task is lacking, however, which highlights the role of all disciplines involved in the creation and use of corrosion protection coatings for metals. Fouling is the process of accumulating unwanted material that is mostly non-living and comprised of detritus and organic or inorganic compounds, or organisms, such as tiny viruses up to giant kelps. This book covers both the processes of biofouling and anti(bio)fouling, and the devices that stop the biofouling process. This book provides a missing synopsis by providing an understanding of the anticorrosive and anti-biofouling effects of nanomaterials and nanocomposites under different environments. It features an up-to-date picture of the quality and chemistry of a substrate surface, its proper preparation by conversion treatment, the function of resins and anticorrosive pigments in paints, and novel concepts for corrosion protection. 2024 Scrivener Publishing LLC.