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A Comparative Study of the Nonlinear Optical Properties of CaO Nanoparticles and rGO-CaO Nanocomposites
Recently, graphene-based materials decorated with metal/metal oxide nanoparticles have gained significant interest among researchers owing to their wide range of technological applications. In this study, we synthesized reduced graphene oxide-calcium oxide nanocomposites (rGO-CaO) using a one-pot solvothermal technique. The third-order nonlinear optical (NLO) properties of CaO nanoparticles and (rGO-CaO) nanocomposites were explored by performing a single-beam Z-scan experiment. Since the samples exhibited reverse saturation absorption behavior (RSA) and a negative nonlinear index of refraction, CaO nanoparticles are promising candidates for nonlinear optical limiting and optical switching applications. Indian Association for the Cultivation of Science 2024. -
A Comparative Study of the Nonlinear Optical Properties of CaO Nanoparticles and rGO-CaO Nanocomposites
Recently, graphene-based materials decorated with metal/metal oxide nanoparticles have gained significant interest among researchers owing to their wide range of technological applications. In this study, we synthesized reduced graphene oxide-calcium oxide nanocomposites (rGO-CaO) using a one-pot solvothermal technique. The third-order nonlinear optical (NLO) properties of CaO nanoparticles and (rGO-CaO) nanocomposites were explored by performing a single-beam Z-scan experiment. Since the samples exhibited reverse saturation absorption behavior (RSA) and a negative nonlinear index of refraction, CaO nanoparticles are promising candidates for nonlinear optical limiting and optical switching applications. Indian Association for the Cultivation of Science 2024. -
A Comparative Study of Thermoconvective Flows of a Newtonian Fluid Over Three Horizontal Undulated Surfaces in a Porous Medium
This paper presents a comparison between the results of three thermoconvective flows of a Newtonian fluid over uniformly heated, undulated horizontal surfaces in a porous medium against the background of the results of a flat plate. The undulations are assumed to have sinusoidal, sawtooth, and triangular waveforms. A system of nonlinear coupled partial differential equations arising in the study is solved using the KellerBox method. Streamlines and isotherms have been plotted and analyzed to examine the effect of parameters on the fluid dynamics and heat transfer. At large surface amplitudes, secondary flow is observed in the cases of sinusoidal and triangular waveforms, but not in the cases of a sawtooth surface and a flat plate. The magnitude of the slip velocity at the horizontal surface is greatest for the sine waveform, while it is least in the case of triangular. The flat plate does not support slip in the velocity to the extent seen in the case of undulated surfaces. The variation of the mean Nusselt number and mean skin friction with surface amplitude and the Rayleigh number indicate that heat transfer and viscous friction at the boundary increase with individual and collective increases in the values of the amplitude and the Rayleigh number. Further, the mean Nusselt number and mean skin friction are found to be maximum for the sinusoidal surface and minimum for the triangular one. The heat transfer and skin friction by the flat surface are much less than that of all three undulated surfaces. Copyright VC 2022 by ASME. -
A Comparative Study of Unsupervised Models for Anomaly Detection in Maritime AIS Data
The integrity of global maritime trade is increasingly threatened by deceptive practices such as sanctions evasion and illicit trafficking, often facilitated by the manipulation of vessel tracking data from the Automatic Identification System (AIS). While AIS provides a rich source for monitoring vessel behavior, the vast scale of the data and the novelty of anomalous patterns necessitate advanced, automated detection methods. This paper presents a comprehensive benchmarking study of four dis-tinct unsupervised machine learning architectures for detecting anomalies in historical AIS vessel trajectories. The evaluated models include a Bidirectional GRU (Bi-GRU) autoencoder, a probabilistic GeoTrackNet with A Contrario detection, a two-level grid representation with Isolation Forest, and a multi-model approach combining spatial-thematic attributes with Isolation Forest. We provide detailed mathematical formulations, algorithmic descriptions, and rigorous comparative analysis of each approach, examining trade-offs between temporal modeling, spa-tial context awareness, feature engineering, and computational complexity. Our benchmarking results on 985,700 AIS messages indicate that spatially-aware models (GeoTrackNet, grid-based methods) demonstrate significantly higher sensitivity (6.76%-10.00% anomaly rates) than purely temporal models (0.20%), but at greater computational cost. This study provides practical guidance for model selection based on operational requirements and proposes future directions toward multimodal architectures integrating trajectory analysis with document-based verification. 2025 IEEE. -
A Comparative Study on Blockchain Architectures for Secure and Transparent Healthcare Systems
The research compares blockchain technologies in the healthcare industry, focusing on data security, decentralization, and transparency for managing data. Traditional healthcare systems face challenges, notably data breaches, inefficiencies in maintaining records, less interoperability, and issues regarding patient privacy. The solution with the use of the distributed nature of blockchain as an advantage is to provide a secure, decentralized space to store and manage medical data that is sensitive for creating a transparent, tamper-proof ledger accessible only by individuals or parties that are authorized. This paper highlights a comprehensive study of several blockchain architectures and applications in industry, such as electronic health records (EHRs), securing patient identity, tracking of drug supply chain, and secure medical data sharing. The approaches enhance data security and provide a transparent and trustworthy record of all data within a system. After analyzing numerous mechanisms and encryption approaches and combining blockchain with emerging technologies such as artificial intelligence (AI) and the Internet of Things (IoT), this chapter surveys blockchains prospect of enhancing healthcare efficiency while holding security and regulatory compliance. Likewise, the chapter discusses the restrictions of blockchain, including scalability, computational expenses, and lawful challenges, providing an understanding of forthcoming study trends and adoption methods for blockchain-based healthcare solutions. 2026 Anindya Nag, Md. Mehedi Hassan, Riya Sil and Asif Karim. -
A comparative study on decision tree and random forest using konstanz information miner (KNIME)
With vast amounts of data floating around everywhere, it is imperative to comprehend and draw meaningful insights from the same. With the proliferation of Internet and Information Technology, data has been increasing exponentially. The 5 Vs of data i.e. Value, volume, Velocity, variety and veracity will only make sense if we are able to examine the data and uncover the hidden, yet meaningful insights. With large data becoming a norm, a lot of data mining algorithms are available that help in data mining. We have tried to compare two classification algorithms, primarily Decision trees and Random forest. A total of 10 datasets have been taken from UCI Repository and Kaggle and with the help of Konstanz Information Miner (KNIME) workflows, a comparative performance has been made pertaining to the accuracy statistics of Random Forest and decision Tree. The results show that Random Forest gives better and accurate results for a dataset as compared to decision trees. 2020 SERSC. -
A comparative study on e-waste management systems in developed and developing countries: Legislative compliances and initiatives
E-waste is an ongoing issue that still lacks a suitable solution, particularly in developing nations. The environment and human health have suffered dramatically as a result of poor recycling practices of waste of electrical and electronic equipment (WEEE), transboundary movement, improper management of e-waste, the lack of environmentally sound management (ESM) programs, and the ineffective EPR (extended producer responsibility) schemes. Although developed nations have implemented efficient legislative frameworks and regulations, emerging nations suffer due to their plans. E-waste management systems differ in developed and developing countries; thus, this study evaluates the differences between the management systems and outlines the areas where the developing nations lack effective e-waste management and the advantages developed countries enjoy. Therefore, the current study results are crucial for comprehending the severe hazard posed by improper management of e-waste and the viability of future research into creating strategies to address these problems of developing nations. 2023, IGI Global. -
A Comparative Study on Indian Sign Language Representation
Communication among people can happen with the help of verbal or nonverbal language. Nonverbal communication is shared only among the hearing and speech impaired and is not common among others. Non-verbal communication is also different for different countries around the world. A solution to remove the gap between verbal and non-verbal communicators is to create an automated language translation model that can effortlessly convert sign language to text or audio. This area has been under research for a long time, but an economical and robust system that can efficiently convert signs into speech still does not exist. This paper focuses on different approaches that were put forward to turn Indian sign language into audio signals. The Sign Language Recognition (SLR) system is classified as isolated and continuous sign language models based on its input. 2021 IEEE. -
A Comparative Study on IOT Security Using Machine Learning Techniques
This increased reliance on networks has made the security of IoT devices a highly burning issue. Among the sea of threats, the threats associated with DDoS attacks are at a high level since they do damage to the functionality of devices and unavailability of networks. Detection and mitigation of DDoS attacks will demand IoT environments based on powerful classification algorithms. This paper evaluates the performances of three prominent algorithms: Decision Tree, Random Forest, and Histogram-Based Gradient Boosting for the classification of DDoS attack traffic within IoT networks. An IoT-23 dataset comprising a subset of attacks, including DDoS, is used herein for the purpose of achieving high classification accuracy to ensure a reliable evaluation of attacks. The results clearly show that all three algorithms are pretty good in terms of detection performance, and Histogram-Based Gradient Boosting is the best in terms of generalization accuracy. These results open new perspectives for the implementation of machine learning, generally, and Histogram-Based Gradient Boosting, specifically, directed to improving security in IoT networks against DDoS attacks, which is an extremely promising result when working within the light of some insights for future research and development within this critical area of security. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
A comparative study on the adaptability of the different varieties of solanum lycopersicum L. (tomato) in salt stress condition
The objective of the present study was to study the levels of antioxidant and oxidant metabolites such as total protein, proline, peroxidase, lipid peroxidase, catalase,and anthocyanin and phenol contents in nine varieties of tomato plants (Cerasiforme (Cherry tomato), Indamrohini, Marglobe, Ns 538, Sacchariya, San Marzano 3, Suhyana, Tomato Oblate Yellow, Vanda) treated under various NaCl concentrations (50, 100, 200 and 250 Mm). Salinity is one of the significant abiotic stresses, which affects plant cell metabolism and reduces plant productivity. Plants tolerant to NaCl implement a series of adaptations to acclimate to salinity, including morphological, physiological and biochemical changes. Under saline conditions, plants have to activate different physiological and biochemical mechanisms in order to cope with the resulting stress. Such mechanisms inclu de changes in morphology, anatomy, water relations, photosynthesis, the hormonal profile, toxic ion distribution and biochemical adaptation (such as the antioxidative metabolism response). An updated discussion on salt-induced oxidative stress and its effect on the antioxidant machinery in both salt-tolerant and salt-sensitive plants is the major part of this study. The aim of the present study is to extend our understanding of how salinity may affect the physiological characteristics of plants. 2020 IJSTR. -
A comparative study on the effect of HNT and nano-alumina particles on the mechanical properties of vacuum bag moulded glass-epoxy nanocomposites
In the present work, the mechanical properties of the Halloysite nanotube (HNT) and Nano-Alumina particle additions in glass-epoxy nanocomposites are investigated experimentally. The composite specimens for tensile, flexural, interlaminar shear strength (ILSS) and impact tests are prepared by vacuum bag moulding process and tested in accordance with the ASTM standards. HNT/Nano-Alumina particle contents are varied from 0 to 4 wt. %, while the weight fraction of glass fiber is kept constant at 60%. The strength values of the respective tests are obtained and compared graphically to study the effect of nanoparticle type and content on the mechanical properties. From the experimentation and subsequent result analysis, considerable improvements in the mechanical properties are observed with the addition of nanoparticles as compared to neat composites. The 3 wt.% addition of HNT in the nanocomposites resulted in increase in tensile strength, elastic modulus, flexural strength, flexural modulus, ILSS and impact energy values by 12.7%, 6.96%, 5.46%, 4.49%, 7.44% and 119.3% respectively in comparison with the same weight percentage of Nano-Alumina. HNT modified composites reveal an improvement in mechanical properties, hence qualifying it as a most promising cost-effective reinforcing filler for glass-epoxy composites. Further, the SEM micrographs of fractured surfaces are analyzed to study the failure mechanisms and fracture morphologies of higher loaded composites (4 wt.%) and understand the reason for decline in mechanical properties. 2021 Published by Semnan University Press. All rights reserved. -
A comparative study on the moderating impact of renewable energy and innovation on environmental quality
This study explores the complex interactions between renewable energy production, innovation, economic growth, institutional quality, economic globalization, and CO2 emissions in OECD countries and emerging economies from 1996 to 2021. Results from DriscollKraay standard error and feasible generalized least square reveal distinct trends: renewable energy production leads to increased CO2 emissions in emerging economies but significantly reduces emissions in OECD countries. Besides, residential and non-residential innovation, along with total innovation, show similar effects. Notably, technology-moderated renewable energy production effectively lowers CO2 emissions in both country groups. Similarly, economic growth enhances environmental quality in both sets of countries. However, institutional quality needs improvement in emerging economies, while current levels suffice in OECD nations to maintain environmental quality. Moreover, the study emphasizes the importance of considering globalization's impact on CO2 emissions, advocating for international agreements to leverage globalization for environmental benefits. Overall, these findings provide valuable insights for shaping renewable energy policies, fostering innovation, promoting economic growth, enhancing institutional quality, and harnessing globalization efforts to reduce CO2 emissions and enhance environmental quality. 2024 United Nations. -
A comparative study on the moderating impact of renewable energy and innovation on environmental quality
This study explores the complex interactions between renewable energy production, innovation, economic growth, institutional quality, economic globalization, and CO2 emissions in OECD countries and emerging economies from 1996 to 2021. Results from DriscollKraay standard error and feasible generalized least square reveal distinct trends: renewable energy production leads to increased CO2 emissions in emerging economies but significantly reduces emissions in OECD countries. Besides, residential and non-residential innovation, along with total innovation, show similar effects. Notably, technology-moderated renewable energy production effectively lowers CO2 emissions in both country groups. Similarly, economic growth enhances environmental quality in both sets of countries. However, institutional quality needs improvement in emerging economies, while current levels suffice in OECD nations to maintain environmental quality. Moreover, the study emphasizes the importance of considering globalization's impact on CO2 emissions, advocating for international agreements to leverage globalization for environmental benefits. Overall, these findings provide valuable insights for shaping renewable energy policies, fostering innovation, promoting economic growth, enhancing institutional quality, and harnessing globalization efforts to reduce CO2 emissions and enhance environmental quality. 2024 United Nations. -
A Comparison of 2 Step Classification with 3-Class Classification for Webpage Classification
The content over internet increasing significantly each year and the web page classification is an essential areas of work upon for web-based information management, content retrieval, data scrapping, content filtering, advertisement removal, contextual advertising, expanding web directories etc. Multiclass classification methods is more popular and commonly use to classify web pages, and 2 step classification is our proposed system. In 2 step classifier, we use 2 primary model which works serially and perform binary classification at each level. The primary source of dataset contain thousands of URL(Uniform Resource Locator) of web pages. The content on webpage is extracted and stored on system to avoid the loss of data sue to the change in URL. The comparison between the two methods validated the system improvement and improved in different metric such as precision and recall using 2 step classification technique. 2 step classification technique is faster while training and also shows performance improvement. There proposed system shows improvement in the performance of the results but not something significant. 2022 IEEE. -
A comparison of algorithms for controller replacement in software defined networking
Software Defined Network (SDN) partitions the control plane and the information plane to decrease the cost and for increasing the capacity for upgrading, and this will be helpful for the network administrators to manage the network services. It's the location where the controller exists. One of the main issue in Software Defined Networking is the location of the controllers as this could affect network execution and cost. In this paper, we have done an analysis on some algorithms that have been used for minimizing the number of controllers to reduce the latency, delay, etc. while placing a controller with the consideration of communication among the controller and the nodes. 2018 Authors. -
A comparison of in vitro cytotoxicity of undoped and doped surface modified CaS nanoparticles
In the present study we compare the cytotoxicity of undoped and doped surface modified CaS nanoparticles synthesized by wet chemical co-precipitation technique using L929 human fibroblasts cell lines. The toxicity was determined by evaluating the cell viability and changes in cell morphology. In addition, the half-maximal inhibitory concentration (IC50) values for all the samples were also compared. This analysis shows that undoped and terbium doped TEOA capped CaS nanoparticles are more biocompatible and will be better candidates for various applications in the biomedical field. 2021 Elsevier B.V. -
A comparison of recommendation algorithms based on use of linked data and cloud
Recommendation generation is a critical need in today's time. With the advent of big data and the increasing number of users, generation of most suitable recommendation is essential. There are many issues already associated with recommendations such as data acquisition, scalability, etc.. Moreover, the users today look to get best recommendations at the minimum effort on their side. Thus it becomes difficult to manage such huge amount of information, extract the needed data and present it to the user with least user involvemen t. In this research, we surveyed some recommendation algorithms and analyze their applications on an open cloud server which uses linked data to generate automated recommendations. 2018 Authors. -
A Comparison of Similarity Measures in an Online Book Recommendation System
To assist users in identifying the right book, recommendation systems are crucial to e-commerce websites. Methodologies that recommend data can lead to the collection of irrelevant data, thus losing the ability to attract users and complete their work in a swift and consistent manner. Using the proposed method, information can be used to offer useful information to the user to help enable him or her to make informed decisions. Training, feedback, management, reporting, and configuration are all included. Our research evaluated user-based collaborative filtering (UBCF) and estimated the performance of similarity measures (distance) in recommending books, music, and goods. Several years have passed since recommendation systems were first developed. Many people struggle with figuring out what book to read next. When students do not have a solid understanding of a topic, it can be difficult determining which textbook or reference they should read. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A comparitive study on traditonal healthcare system and present healthcare system using cloud computing and big data
Cloud computing is one the emerging technology which provides all the necessary resources required for day to day operations of an organization in a virtual environment. It is also known as green computing as it reduces the physical existence of the hardware resources. Health is being considered as a basic right for an individual. Even though there are advancements in the healthcare sector of India when compared to earlier stages, there is still a need for betterment in this sector. In order to make progress in this field, constant learning and better economic standards are needed. This paper provides a comparative view of the progress made by India in the healthcare sector after the introduction of two major technologies such as cloud computing and big data. 2017 IEEE. -
A Compartmental Mathematical Model of Novel Coronavirus-19 Transmission Dynamics
The COVID-19 pandemic has spread quickly throughout the world, posing a serious threat to human-to-human transmission. The novel coronavirus pandemic is described quantitatively in this paper using a mathematical model of COVID-19 driven by a system of ordinary differential equations. The suggested model is used to provide predictions regarding the behavior of a COVID-19 outbreak over a shorter time frame. It is demonstrated that the system of model equations has a unique and existing solution. Furthermore, the answer is positive and bounded. Thus, it is argued that the model created and discussed in this work is both mathematically and biologically sound. A threshold parameter that controls the disease transmission is used in a qualitative analysis of the model to confirm the existence and stability of disease-free and endemic equilibrium points. Additionally, the key parameters undergo sensitivity analysis to ascertain their relative significance and potential influence on the COVID-19 virus dynamics. 2024 NSP Natural Sciences Publishing Cor.