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An Efficient Security-Enabled Routing Protocol for Data Transmission in VANET Using Blockchain Ripple Protocol Consensus Algorithm
The security quality in Vehicular Ad-hoc NETworks (VANET) has improved as a result of recent developments in Intelligent Transportation Systems (ITS). However, within the current VANET system, providing a cheap computational cost with a high serving capability is a significant necessity. When a vehicle user goes between one Roadside Unit (RSU) to another RSU region in the current scenario, the current RSU periodically needs re-authentication of the vehicle user. This increases the computational complexity of the system. The gathering and broadcast of existing traffic event information by automobiles are critical in Vehicular Ad-hoc Networks (VANET). Traditional VANETs, on the other hand, have several security concerns. This work develops a blockchain-based authentication protocol to address the aforementioned difficulty. To address critical message propagation issues in the VANET, we invent a novel type of blockchain. We develop a local blockchain for exchanging real-world event messages among cars within a countrys borders, which is a novel sort of blockchain ideal for the VANET. We describe a public blockchain RPCA that records the trustworthiness of nodes and messages in such a distributed ledger suitable for secure message distribution. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
An Efficient Sorting Algorithm for Capacitor Voltage Balance of Modular Multilevel Converter With Space Vector Pulsewidth Modulation
Thisarticle presents an efficient analogue sorting algorithm for balancing the submodule (SM) capacitor voltages of modular multilevel converter (MMC). The proposed analogue sorting algorithm offers the advantage of fast convergence rate without any need of recursive loops for the implementation on embedded devices. It can be easily implemented with combinational logic operations on field programmable gate array (FPGA) and provides less hardware and computational overhead. The functionality and performance of the proposed analogue sorting algorithm is evaluated with the simulation model of three phase five-level MMC in MATLAB/Simulink environment. The real time implementation of the proposed sorting algorithm with the SM capacitor voltage balancing strategy is implemented on Altera/Cylone - I (EP1C12Q240C8N) FPGA. A five-level continuous space vector pulsewidth modulation (CSVPWM) is realized on a PIC microcontroller (PIC18F452). A down-scaled model of single-phase five-level MMC is designed and constructed to investigate the reliable and stable operation of MMC with the proposed analogue sorting algorithm and SVPWM method. Simulation and experimental results are presented for validation. 1986-2012 IEEE. -
An efficient technique for generalized conformablePochhammerChree models of longitudinal wave propagation of elastic rod
In this article, we introduce analytical-approximate solutions of time-fractional generalized Pochhammer-Chree equations for wave propagation of elastic rod by means of the q-homotopy analysis of the transform method (q-HATM). In the Caputo sense, basic concepts for fractional derivatives are defined. Several examples are given and the results are illustrated via some surface plots to present the physical representation. The results show that the current methodology is productive, powerful, efficient, easy to use, and ready to incorporate a wide variety of partial fractional differential equations. 2022, Indian Association for the Cultivation of Science. -
An Efficient Technique for One-Dimensional Fractional Diffusion Equation Model for Cancer Tumor
This study intends to examine the analytical solutions to the resulting one-dimensional differential equation of a cancer tumor model in the frame of time-fractional order with the Caputo-fractional operator employing a highly efficient methodology called the q-homotopy analysis transform method. So, the preferred approach effectively found the analytic series solution of the proposed model. The procured outcomes of the present framework demonstrated that this method is authentic for obtaining solutions to a time-fractional-order cancer model. The results achieved graphically specify that the concerned paradigm is dependent on arbitrary order and parameters and also disclose the competence of the proposed algorithm. 2024 The Authors. -
An efficient technique to analyze the fractional model of vector-borne diseases
In the present work, we find and analyze the approximated analytical solution for the vector-borne diseases model of fractional order with the help of q -homotopy analysis transform method ( q -HATM). Many novel definitions of fractional derivatives have been suggested and utilized in recent years to build mathematical models for a wide range of complex problems with nonlocal effects, memory, or history. The primary goal of this work is to create and assess a Caputo-Fabrizio fractional derivative model for Vector-borne diseases. In this investigation, we looked at a system of six equations that explain how vector-borne diseases evolve in a population and how they affect community public health. With the influence of the fixed-point theorem, we establish the existence and uniqueness of the models system of solutions. Conditions for the presence of the equilibrium point and its local asymptotic stability are derived. We discover novel approximate solutions that swiftly converge. Furthermore, the future technique includes auxiliary parameters that are both trustworthy and practical for managing the convergence of the solution found. The current study reveals that the investigated model is notably dependent on the time chronology and also the time instant, which can be effectively studied with the help of the arbitrary order calculus idea. 2022 IOP Publishing Ltd. -
An Efficient Underwater Image Restoration Model for Digital Image Processing
Digital image processing (DIP) is showing a massive growth intodays trending world particularly, in the field of biological research. Underwater image analysis plays a vital role, where the images are easily prone to attenuation and haziness. Capturing underwater images has always been a challenging job due to dispersion and scattering of light inside water on a high scale. Several image enhancement and restoration methodologies are currently available to address these issues, where hazing and color diffusion are viewed as a common phenomenon in it. Such procedures normally includes two basic methodologies in it, namely dehazing and contrast or color enhancement, which improves the overall output of the degraded image. However, the quality and processing time of the images can still be enhanced with additional techniques incorporated to it. This work is intended toward proposing one such channel called improvised bright channel prior for dehazing the underwater images. The technique further improves on the existing methodologies by estimating the atmospheric light and refining the transmittance of the image along with image restoration. The experimental results show that the improvised bright channel prior methodology is found to perform better in dehazing underwater images with a balanced intensity in terms of dark and white patches obtained from it. When comparing and contrasting the processing time of the proposed methodology with the existing techniques, it is found that improvised bright channel prior performs better. Also, the quality of the dehazed underwater image obtained from the proposed channel is found to be effective when compared with the existing channels. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
An Efficient Wireless Sensor Network based Intrusion Detection System
Wireless Sensor Networks (WSNs) are widely used in diverse applications due to their cost-effectiveness and versatility. However, they face substantial difficulties because of their innate resource constraints and susceptibility to security attacks. A possible method to improve the security of WSNs is clustering-based intrusion detection and responding mechanisms. An in-depth analysis of the clustering-based intrusion detection and response method for WSNs is presented in this study. The suggested method efficiently uses data mining and machine learning techniques to identify unusual behaviour and probable intrusions. The system effectively analyses data inside clusters by grouping Sensor Nodes (SN) into clusters, allowing it to differentiate between legitimate patterns and insecure activity. The network may respond promptly to identified breaches and react to the responsive mechanism, which reduces their impact and protects network integrity. The proposed Mathematically Modified Gene Populated Spectral Clustering Based Intrusion Detection System and Responsive Mechanism (MMMMGPSC-IDS-RM) is compared with existing state-of-art techniques, and MMMMGPSC-IDS-RM outperforms with the highest detection rate of 96%. 2023 IEEE. -
An efficient ZnO and Ag/ZnO honeycomb nanosheets for catalytic green one-pot synthesis of coumarins through Knoevenagel condensation and antibacterial activity
This study pioneers the synthesis of porous Ag/ZnO nanosheets, focusing on their role as a catalyst in Knoevenagel condensation. Notably, these nanosheets display exceptional catalytic efficacy and captivating antibacterial properties. The research delves into the Ag/ZnO catalyst's recyclability and proposes a potential reaction mechanism, marking the first comprehensive exploration of Knoevenagel condensation on porous Ag/ZnO nanosheets. Key findings underscore the successful synthesis of coumarin derivatives using various o-hydroxy benzaldehyde and 1,3-dicarbonyl compounds, with nano-Ag/ZnO serving as a catalyst via a monomode microwave-assisted approach. X-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FE-SEM), Transmission Electron Microscopy (TEM) and UV-Vis spectroscopy were used in conjunction with other physicochemical methods to characterize the synthesized catalytic samples. The method boasts advantages such as high product yields, brief reaction durations, and the ability to reuse the catalyst for multiple cycles. The Ag/ZnO nanosheets, functioning as an acid catalyst, activate carbonyl groups and facilitate their interaction with methylene-containing active molecules. In addition, antibacterial activity assessments demonstrate the superior effectiveness of Ag/ZnO nanocomposites compared to ZnO nanosheets against Staphylococcus aureus germs. This multifaceted study not only advances catalytic synthesis but also unveils promising biological applications of porous Ag/ZnO nanosheets. 2024 Walter de Gruyter GmbH, Berlin/Boston 2024. -
An electrochemical sensor for nanomolar detection of caffeine based on nicotinic acid hydrazide anchored on graphene oxide (NAHGO)
A simple modified sensor was developed with nicotinic acid hydrazide anchored on graphene oxide (NAHGO), by ultrasonic-assisted chemical route, using hydroxy benzotriazole as a mediator. Structural and morphologies of NAHGO samples were investigated in detail by Fourier-Transform Infrared spectroscopy (FT-IR), Powder X-ray diffraction (P-XRD), Raman spectroscopy, Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and Thermogravimetric analysis (TGA). The detailed morphological examination and electrochemical studies revealed the delaminated sheet with the tube-like structure of NAHGO provided the route for more electroactive surface which influenced the electrooxidation of caffeine with increased current. The electrochemical behaviour of NAHGO on a glassy carbon electrode (GCE) for caffeine detection was demonstrated by employing voltammetric techniques. The influence of scan rate, pH, and concentration on caffeine's peak current was also studied. The NAHGO sensor was employed for the determination of caffeine in imol plus and energy drinks. The detection limit determined was 8.7 109M, and the best value was reported so far. The results show that NAHGO modified electrodes are one of the best preferences to establish new, efficient, and reliable analytical tools for the detection of caffeine. 2021, The Author(s). -
An empirical analysis of android permission system based on user activities
In today's world there has been an exponential growth among smart-phone users which has led to the unbridled growth of smart-phone apps available in Google play store, app store etc., In case of android application, there are many free applications for which the user need not shell out a penny to use the services. Here the magic word is "free" which entices millions of pliant people into installing those apps and giving unnecessary access to their data and device control. Current studies have shown that over 70% of the apps in market, request to gather data digressive to the most functions of apps that might cause seeping of personal data or inefficient use of mobile resources. Of late, couple of malignant applications gather unobtrusive information of the user through third-party applications by increasing their permissions to high-level on the Android Operating System. Android permission system provides, the user access to the third party apps and in return based on the permissions granted by the user, an app can access the related resource from the user's mobile. A user is bound to grant or deny permits during the installation of the application. For the most part, users don't focus on the asked permissions, or sometimes users do not understand the meaning of the permission and install the app on their device. They allow a way for attackers to perform the malicious task by demanding for more than expected set of permissions. These extra permissions permit the attacker to exploit the device and also retrieve sensitive information from it. In this research paper we describe how permission system security can create an awareness among the users that would assist them in deciding on permission grants. This improved and responsible user activities in Android OS can help the users in utilizing their device securely. 2018 Ankur Rameshbhai Khunt and P. Prabu. -
An Empirical Analysis of Consumer's Environmental Attitude and Purchasing Behavior of Green Product with Special Reference to Bangalore City
This study examines the consumers attitude and purchasing behavior of green product of Indian consumers. To meet this objective, a structured questionnaire has been used to collect the data samples of 300 respondents. The survey results obtained from Bangalore City provide reasonable support for the validity of the proposed model. The collected data has been filtered and found 261 valid data to carry out the data analysis to find the result and conclusion of this research study. The result of this study, consumers who have positive attitude about the environment are giving more importance to buy eco-friendly product (Green Product) and it is clearly observed that there is a positive relationship between the consumers environmental attitude and purchasing behavior of the green product. This study also outlines the green product categories and examines which category is more preference by the consumers with regards to their gender, age, occupation and income. The green product categories are Grocery Items, Health and Beauty, Apparel, Produce, Cleaning and Households, Pet Products, Meat/Fish and Poultry, Paper Products and Electronics and Appliances. Despite the age, gender, occupation and income differences, it is found that majority of the consumer preference to buy Electronics and Appliances and Health and Beauty products out of those green product categories. Even though they also buy other category of the green product but the counts are minimal as compare to Electronics and Appliances and Health and Beauty Products. Furthermore, this study also discusses the different factors that impact on buying decision taken by the consumers. This study specifically studied with three main factors that influence the purchasing decision of the consumer regarding the eco- friendly product. These are constant factor such as Price and Quality; Brand and Environmental Factors. -
An Empirical Analysis of Factors and Variables Influencing Internet Banking among Bangalore Customers
International Journal of Research in Computer Application & Management, Vol. 2, Issue 10, pp. 143-148, ISSN No. 2231-1009 -
An empirical analysis of ICT tools with gamification for the Indian school education system
Information and communication technologies (ICTs) are used as a part of different fields, for example, training, business, and healthcare. The main objective of this paper is to introduce ICT as a better method to teach and test student's performance so it can become a part of the school curriculum and enhance learner's experience. To accomplish this objective, multiple kinds of literature were studied to get insights into the factors associated with ICT and gamification. Based on the findings, a survey was conducted on teachers to know the favourability of ICT in modern schools. Based on the response, two application prototypes are developed for students to get their performance and results that support the study. Most importantly, similar concepts were taught to students using both, traditional and ICT based approaches. A test was conducted via both methods. It was discovered that the performance of the students increased by 13% when the modern approach was followed to conduct the test. Copyright 2021 Inderscience Enterprises Ltd. -
An Empirical Analysis of Price Discovery in Spot and Futures Market of Gold in India
The broadest classification of the Indian financial market can be made in terms of commodity market, stock and security markets and foreign exchange market. Commodity markets are markets where raw or primary products are exchanged. These raw commodities are traded on regulated commodity exchanges, in which they are bought and sold in standardized contracts. Gold is a commodity which has been undergoing very serious price fluctuations in recent years. It has had its own impact on commodity trading too. Price discovery process of gold has always been a matter of wide discussion among researchers and policy makers. In this context this study aims at analyzing the price discovery process of Gold in Indian commodity market. It also looks into the volatility impact of futures price on spot price as well as the volatility impact of spot price on futures price. The study is completely based on the secondary data collected from the official website of NCDEX. The data extend for a period ranging from 23rd April 2009 to 29th December 2011. The daily data of spot and futures prices of gold during the period is taken into account. Various econometric tools are employed to test the hypotheses set. The VAR model result confirms the unidirectional relationship runs from the spot market to the futures market of gold in India. It reveals co integration and dynamic relationship between spot and futures markets of gold. The result of GARCH model implies that both futures as well as spot markets do have significant impact in the price volatility of gold in India. The result of VECM tells that spot market is dominant in the price discovery process which is a clear indication of the fact that spot market of gold is information efficient in India. The result is of great significance for the investors who wish to improve portfolio performance. With regard to policy making, a better understanding of the interconnectedness of these markets would be useful for the policy makers who coordinate the stability of financial markets. For marketers, it provides a reliable forecast of spot prices in the future to allow them to effectively manage their risks in the production or marketing process. The unprecedented uptrend in the price of gold and high volatility in recent years provides room for some important social implications. -
An empirical analysis of price discovery in spot and futures market of gold in India /
Pacific Business Review International, Vol.7, Issue 10, pp.80-88 -
An empirical analysis of similarity measures for unstructured data
With fast growth in size of digital text documents over internet and digital repositories, the pools of digital document is piling up day by day. Due to this digital revolution and growth, an efficient and effective technique is required to handle such an enormous amount of data. It is extremely important to understand the documents properly to mine them. To find coherence among documents text similarity measurement pays a humongous role. The goal of similarity computation is to identify cohesion among text documents and to make the text ready for the required applications such as document organization, plagiarism detection, query matching etc. This task is one of the most fundamental task in the area of information retrieval, information extraction, document organization, plagiarism detection and text mining problems. But effectiveness of document clustering is highly dependent on this task. In this paper four similarity measures are implemented and their descriptive statistics is compared. The results are found to be satisfactory. Graphs are drawn for visualization of results. 2019 COMPUSOFT, An international journal of advanced computer technology. -
An empirical analysis of similarity measures for unstructured data /
An International Journal of Advanced Computer Technology, Vol.8, Issue 8, pp.3302-3306, ISSN No: 2320-0790. -
An empirical analysis of sustainability of public debt among BRICS nations
The main objective of this paper is to verify the sustainability of public debt among Brazil, Russia, India, China and South Africa (BRICS) in a political economy framework. Annual panel data have been used for BRICS countries from World Development Indicators of World Bank for the period 19802017 for the analysis. Bohn's sustainability framework is used to examine the sustainability of public debt in BRICS nations and verify the influence of political economic variables such as election year, coalition dummy, ideology of the government and unemployment on public debt sustainability. The results suggest that public debt sustainability is weak for BRICS as a whole. China and India have a better public debt sustainability coefficients compared to the same for Brazil, Russia and South Africa. Structural change dummy included in the model suggests that debt sustainability is severely affected after the 2008 crisis period. Political factors have influence on debt sustainability in BRICS. Electoral cycle year and coalition dummy variables adversely affect public debt sustainability in BRICS. While centrist political ideology is found to be significant and negative, left and right ideologies are not significant for debt sustainability. Since debt sustainability is found to be weak in BRICS, countries in the region need to adopt necessary measures to improve their primary balance through appropriate fiscal and debt management. Besides, it is important for the governments to prioritize fiscal prudence irrespective of their ideologies and political compulsions. 2020 John Wiley & Sons, Ltd -
An empirical analysis of the antecedents and barriers to adopting robo-advisors for investment management among Indian investors
This study aims to provide a research framework to understand the antecedents and barriers to adopting Robo-advisors for investment decision-making in India. The study employed a research model based on the extended UTAUT 2, along with three additional constructs, i.e. personal innovativeness (PI), perceived risk (PR), and technological anxiety (TA). Data collected were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) with the help of SmartPLS 4.0 software. This research will help banks, wealth management service providers, FinTech companies, and Robo-advisor developers improve their platforms, offers, products, and marketing tactics for these automated advisory services. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
An Empirical Analysis of Turnaround and its Benefits to Stakeholders
International Journal of Applied Management Research, Vol-6 (1(3), pp. 470-473. ISSN-0974-8709