Volatility Clustering in Nifty Energy Index Using GARCH Model

Volatility has become increasingly important in derivative pricing and hedging, risk management, and portfolio optimisation. Understanding and forecasting volatility is an important and difficult field of finance research. According to empirical findings, stock market returns demonstrate time variable volatility with a clustering effect. Hence, there is a need to determine the volatility in Indian stock market. The authors use Nifty Energy data to analyse volatility since the Nifty Energy data can to be used to estimate the behaviour and performance of companies that represents petroleum, gas, and power sector. The results reflect that Indian stock market has high volatility clustering

RSS Using Social Networks User Profile

E-commerce application in recent days are gaining more importance due to its worldwide services and user-friendly applications. Some of the social networking applications are being backbone of e-commerce applications help in its functioning. With this, the number of e-commerce applications are being associated with social networking site and their user profiles. E-commerce sites use this social networking sites as service providers to their customers associated with their social networking profiles. In these online transactions, social networking sites act as third-party service providers to its users with respect to e-commerce interactions. Social networking sites acting as third-party service providers should be careful about users type, their behaviour and services that they provide. Users choosing their services should also be careful about what to choose and what not to choose. In this three-tier interactions, trust plays a very important role. Trust on any service providers should be evaluated to stay away from online fraudulent activities. User interacting through these applications should always be able to decide between the trusted services and fraud services. Hence, service selection in social networking is proposed with the help of Refined Service Selection (RSS) algorithm using social networks user profiles. Implementation is done with the help of real data set and found that the accuracy of RSS is more when compared with the existing algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd

Bernoulli wavelets functional matrix technique for a system of nonlinear singular Lane Emden equations

In the present paper, we developed the functional matrix of integration via Bernoulli wavelets and generated a competent numerical scheme to solve the nonlinear system of singular differential equations which is Lane Emden form by Bernoulli wavelets collocation technique (BWCT) with different physical conditions. The system of nonlinear singular models is not smooth to operate as they are singular and nonlinear. This approach obtains the solution for this system by transforming it into an a-nonlinear system of algebraic equations by expanding through Bernoulli wavelets with unknown coefficients. These unknown coefficients are calculated using the collocation scheme. The consistency and proficiency of the developed approach are demonstrated via graphs and tables. Attained results confirm that the newly implemented approach is more effective and accurate than other techniques which are available in the literature. All computations have been made using Mathematica software. The convergence of this method is explained in terms of theorems

A survey on blockchain-based student certificate management system

Blockchain Technology's first application is Bitcoin. It started its journey with cryptocurrency in 2008 by Satoshi Nakamoto. After that, it travelled in many areas such as Government, healthcare, academics, supply chain management, Intellectual property management, social welfare, and energy system. Australia, UAE, Japan are some of the top countries using blockchain technology in various government projects. One can use blockchain technology with decentralised storage of data, which is distributed, immutable, tamper resistance, and securable with a consensus mechanism. Today, many government sectors, organisations, companies, and institutions follow blockchain technology using smart contracts that do not require third-party agreements. We have conducted a systematic survey on blockchain-based digital certification to find the research gap in this research work. We carry out the following: (i) Investigation on the reasons to use the blockchain in education system (ii) Classification of blockchain projects into five categories based on services provided by the projects and platforms used for development (iii) Identification of the services provided by the project and the technologies used for the development

Annealing duration dependent optical, nonlinear optical, and optical limiting properties of rare-earth doped glasses embedded with gold nanoparticles

In this work, the Eu2O3 doped B2O3 glass specimen embedded with gold nanoparticles (NPs) was designed by the process of melt-quenching and subjected for thermal treatment to understanding the efficacy of thermal dependency on the optical and nonlinear optical (NLO) characteristics. Linear optical studies have revealed a decrease trend in the energy band gap as the function of annealing duration, indicating the increase of non-bridging oxygen concentration in the glass host. The NLO properties were assessed in near-infrared region utilizing 150 fs laser pulses delivered at the rate of 80 MHz. The aperture free Z-scan measurements exhibited an increased nonlinear absorption coefficient with annealing duration. Further, the closed aperture Z-scan data depicted an increase trend in the positive nonlinear refraction with annealing duration and eventually reduced at the greater duration of annealing. The optical limiting studies demonstrated similar behaviour to the nonlinear absorption characteristics of studied glass samples. These results are related to the local field stimulated by surface plasmons of gold NPs near the Eu3+ ions during the exposure of glass to high fluence laser beam. Our results indicate that B2O3 glasses embedded with Au NPs heat-treated for 30 h at 450 °C are good candidates for nonlinear photonic, optoelectronic, and optical power limiting applications in photonics

Synthesis, characterization of zro₂:Tb³⁺ (1-9 mol %) nanophosphors for blue lighting applications and antibacterial property

This paper reports the structural, morphological, and antibacterial studies of ZrO2:Tb3+ nanophosphors (NPs). The ZrO2:Tb3+ NPs were synthesized by hydrothermal route using Amylamine as surfactant. ZrO2:Tb3+ nanophosphors was characterized by Powder X-ray Diffraction(PXRD), Scanning Electron Microscope (SEM),Diffuse reflectance spectroscopy (DRS), Photoluminescence(PL), Raman spectra, Fourier Transform Infrared radiation(FTIR) and Transmission Electron Microscope(TEM). PXRD analysis shows better crystallinity, cubic in-phase and good homogeneity of the synthesized phosphors were confirmed. When the Tb3+ concentration varies, we obtain blue emissions from ZrO2:Tb3+ NPs. ZrO2:Tb3+ NPs have a promising approach to blue light sources in the display application. SEM images show that ZrO2:Tb3+ nanophosphors have good morphology with a nonporous structure. TEM and SAED pattern confirms that ZrO2:Tb3+ nanophosphors are crystalline in nature. ZrO2:Tb3+ (9mol %) nanophosphors possessed a good antibacterial ability. © 2021 by the authors

A comprehensive review of global alignment of multiple biological networks: background, applications and open issues

Alignment of biological data aims to transfer the functional knowledge across the species by comparing the data of a well-studied one with that of a less-studied thus gaining insights into the cell’s functioning from biological, chemical and physical perspectives. With the advancements in information communication technologies, imaging methods, etc., there is a heap of biological data that is getting accumulated at several databases across the web. This data can be analyzed to attain significant knowledge and to further develop an application that caters to the present and futuristic demands for personalized, preventive and predictive medicine. Global Multiple Biological Network Alignment (GMBNA) is one such technique, where it tries to establishes a relationship between the known and the unknown data and thereby infer knowledge among them. GMBNA, in general, is a sub-graph isomorphism problem that finds the highest degree of correlation among the given networks considering whole network. It is an NP-complete problem, in the past few years, several works have been proposed to address this issue. This paper reviews such existing frameworks for global alignment of multiple biological networks and address many aspects of GMBNA including comparison with other type of alignments, algorithmic implementation, computational challenges, dataset and species considered along with the applications of network aligners across several branches of the bioinformatics. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature

[PDF] from annalsofrscb.ro Predictive Analytics for Sentiment Classification of Social Media Data Using Deep Neural Network

A huge amount of user-generated data in the form of tweets or reviews on social media can be collected and analyzed for making informed decisions. This paper uses the novel deep learning model, namely the Elite Opposition-based Bat Algorithm for Deep Neural Network (EOBA-DNN) for performing polarity classification of the social media data. The proposed method includes three major steps, such as preprocessing, term weighting, and sentiment classification for identifying the polarity of the data. The results show that the EOBA-DNN outperforms other existing algorithms with improved accuracy for Sentiment Classification

Retraction Note to: A Computer Vision-Based Approach for Subspace Clustering and Lagrange Multiplier Optimization in High-Dimensional Data

The publisher would like to alert readers that the conference paper [1] was retracted because of a production error resulting in duplicate publication in the same book series in different volumes. The correct citation for this article should be from the original publication [2]