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Analytical Methods of Machine Learning Model for E-Commerce Sales Analysis and Prediction
In the commercial market, E-commerce sales show a significant trend and have attracted many consumers. Ecommerce sales forecasting has a significant role in an organization's growth and aids in improved operation. Many studies have been conducted in the past using statistical, fundamental, and data mining techniques for better analysis and prediction of sales. However, the current scenario calls for a better study that combines the available information to propose different machine-learning techniques. The sole motive of the study is to analyze and determine different machine learning models to predict accurate results. The research observed that the Extreme Gradient Boosting model outperformed all other models and brought a good result. It produced an RMSE value of 0.0004 and Explained Variance score of 0.99. Decision Tree algorithm also shows an exemplary result. 2023 IEEE. -
Maximum Decision Support Regression-Based Advance Secure Data Encrypt Transmission for Healthcare Data Sharing in the Cloud Computing
The recent growth of cloud computing has led to most companies storing their data in the cloud and sharing it efficiently with authorized users. Health care is one of the initiatives to adopt cloud computing for services. Both patients and healthcare providers need to have access to patient health information. Healthcare data must be shared and maintained more securely. While transmitting health data from sender to receiver through intermediate nodes, intruders can create falsified data at intermediate nodes. Therefore, security is a primary concern when sharing sensitive medical data. It is thus challenging to share sensitive data in the cloud because of limitations in resource availability and concerns about data privacy. Healthcare records struggle to meet the needs of security, privacy, and other regulatory constraints. To address these difficulties, this novel proposes a machine learning-based Maximum Decision Support Regression (MDSR)-based Advanced Secure Data Encrypt Transmission (ASDET) approach for efficient data communication in cloud storage. Initially, the proposed method analyzed the node's trust, energy, delay, and mobility using Node Efficiency Hit Rate (NEHR) method. Then identify the efficient route using an Efficient Spider Optimization Scheme (ESOS) for healthcare data sharing. After that, MDSR analyzes the malicious node for efficient data transmission in the cloud. The proposed Advanced Secure Data Encrypt Transmission (ASDET) algorithm is used to encrypt the data. ASDET achieved 92% in security performance. The proposed simulation result produces better performance compared with PPDT and FAHP methods. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analysis of nonlinear convection and diffusion in viscoelastic fluid flow with variable thermal conductivity and thermal radiations
The study offers a thorough evaluation of the complex fluid dynamics and heat transfer phenomena in Williamson viscoelastic fluid flow, taking into account thermal radiations and variable thermal conductivity. The paper extends its analysis to include heat transfer effects, which are critical in several engineering and industrial applications, and digs into the complexity of non-Newtonian fluid behavior, with a special focus on thermal radiation, heat production, diffusion and viscous dissipation. The study makes use of mathematical models and numerical method RK4 to clarify the nonlinear interactions between convection and diffusion processes in this viscoelastic fluid. The energy and concentration equations are simulated in the presence of the modified Fourier and Fick laws. Moreover, the predicted heat flow is based on the Cattaneo-Christov theory. This research also sheds light on the interaction between rheological properties and thermal characteristics, providing important new knowledge to the broader field of fluid dynamics and heat transfer. 2024 World Scientific Publishing Company. -
Clay-based cementitious nanofluid flow subjected to Newtonian heating
In recent years, a novel technique for producing robust cementitious materials, called nanocomposites, has emerged. These materials are comprised of clay minerals and polymers. As a result, a vertical flat plate has been used to evaluate a clay-based cementitious nanofluid in this research. The impacts of first-order chemical reactions, heat generation/heat absorption, and the Jeffrey fluid model are taken into account for the study of flow. Newtonian heating and the conditions for slippage velocity have also been considered. The mathematical problem for the flow analysis has been established in relations of partially coupled partial differential equations and the model has been generalized using constant proportional Caputo (CPC) fractional derivative. The problem is solved using the Laplace transform technique to provide precise analytical solutions. On the concentration, temperature, and velocity fields, the physics of a number of crucial flow parameters have been examined graphically. The acquired results have been condensed to a very well-known published work to verify the validity of the current work. It is important to note here that the rate of heat transfer in the fluid decreases by 10.17% by adding clay nanoparticles, while the rate of mass transfer decrease by 1.31% when the value of ? reaches 0.04. 2023 World Scientific Publishing Company. -
MHD nanofluid flow through Darcy medium with thermal radiation and heat source
In this analysis, we have considered heat transmission in two-dimensional steady laminar nanouid ow past a wedge. Magnetohydrodynamic (MHD), Brownian motion, viscous dissipation and thermophoresis eects are considered over the porous surface. Similarity transformations have been used to change the governing partial dierential equations (PDEs) into nonlinear higher-order ordinary dierential equations (ODEs). Governing ODEs with boundary conditions are then converted to the system of first-order initial value problem. After that the modeled system is solved numerically by RK4 technique. Impact of the magnetic number, Eckert number, Prandtl number, Lewis number, Brownian motion, thermophoresis and permeability parameters on the ow domain is analyzed graphically as well as in tabular form. It is noted that magnitude of Nusselt number for the ow regime increases with the increase of nondimensional parameter Pr; Nb; Nt while opposite behavior is observed in case of R. World Scientific Publishing Company. -
Heat Convection in a Viscoelastic Nanofluid Flow: A Memory DescriptiveModel
Modeling of physical phenomena with fractional differential equations is as old as modeling with ordinary differential equations. There are two stages in modeling of a memory process. One of them is short with persistent impact and other is usually governed by fractional mathematical model. It is established that fractional models fit the experimental data for the memory phenomena in better way when compared with the ordinary models, particularly in mechanics, psychology and in biology. Fractional model of viscoelastic nanofluid flow through permeable medium is studied in this communication. Convection parameters in the flow domain are used to account for buoyancy forces. The governing flow equations are computed using a numerical algorithm that combines finite difference and finite element techniques. The governing models friction coefficient, Sherwood numbers, and Nusselt numbers are calculated. Change in noninteger numbers behave similarly in concentration, temperature, and velocity fields, according to simulations. It is also noted that heat flux, ?1 and mass flux, ?2 numbers have contradictory effects on friction coefficient. Various flow patterns, particularly in the polymer industry and electrospinning for nanofiber manufacture, can be addressed in a similar manner 2023 L&H Scientific Publishing, LLC. All rights reserved -
A clinical study of hepatitis B
The spread of Hepatitis B, which is a severe and enduring disease that origins from its virus is a vital universal issue. It is assessed that about 70 crore people around the globe are enduring HBV transporters. The medical range of HBV virus series starting with subclinical to severe suggestive hepatitis or, hardly, hazardous hepatitis during the severe point and from the quiet hepatitis B external antigen (HBsAg) transporter state, enduring hepatitis of numerous grades of histologic sternness to cirrhosis and its difficulties during the enduring point. In this research paper, we witness medication, signs, and consequence of Hepatitis B. 2019 by Advance Scientific Research. -
Cloud security based attack detection using transductive learning integrated with Hidden Markov Model
In recent years, organizations and enterprises put huge attention on their network security. The attackers were able to influence vulnerabilities for the configuration of the network through the network. Zero-day (0-day) is defined as vulnerable software or application that is either defined by the vendor or not patched by any vendor of organization. When zero-day attack is identified within the network there is no proper mechanism when observed. To mitigate challenges related to the zero-day attack, this paper presented HMM_TDL, a deep learning model for detection and prevention of attack in the cloud platform. The presented model is carried out in three phases like at first, Hidden Markov Model (HMM) is incorporated for the detection of attacks. With the derived HMM model, hyper alerts are transmitted to the database for attack prevention. In the second stage, a transductive deep learning model with k-medoids clustering is adopted for attack identification. With k-medoids clustering, soft labels are assigned for attack and data and update to the database. In the last phase, with computed HMM_TDL database is updated with computed trust value for attack prevention within the cloud. 2022 -
STRATEGIC PARTNERSHIPS AND REGIONAL RESILIENCE: Exploring the Evolving Landscape of India-Southeast Asia Relations
India and Southeast Asia share an elusive sphere of influence, yet face formidable challenges in realising ambitious goals set for the region. Over the years, Indias foreign policy has progressed from being principled to goal driven and objective oriented. Based on analysis of secondary sources of literature, this chapter traces through the relationship between India and Southeast Asia, highlighting a shared landscape of experiences, weaving socio-cultural practices and further boosting economic and international relations. These historical references have found avenues for remodelling in contemporary times in the form of diplomatic success in varied dimensions of engagements. Drawing from these developments and taking the transformations in the geopolitics of Indo-Pacific region into cognizance, this chapter envisions the future prospects for India and Southeast Asia through the lens of building community resilience, promoting its potential to guide regional development and explore the sustainability of social, economic and environmental systems to manage change. This renewed line of thought supports a new analytic of governance which advocates that the local define the configurations and prospects for sustainability of policy frameworks and agreements in the global system. Thus, in the background of the rising traditional and non-traditional challenges, this chapter contributes to a better understanding of change and complexity through a revitalised scope for coordination, cooperation and pragmatism in partnership between the countries. 2024 Taylor & Francis. -
Understanding the social identity of adolescents in the Indigenous Kodava Community of India
The social identity development of adolescents in marginalized communities across the globe holds paramount significance in determining the overall well-being of its future population. Focusing on one such community, the Kodavas, an Indigenous community in South India, this study aims to understand the shifting configurations of social identity based on the changing sociocultural structure and its implications on identity perception among the adolescents belonging to the Kodava community in Kodagu district in Karnataka, India. This study used a qualitative research design to develop an analytical framework of social identity formation and its transitions in the context of the Kodavas. Data were collected from 188 adolescents (47% boys, 53% girls) between 13 and 17 years (M age = 15 years), in the form of essay writing. The findings based on thematic analysis highlight the core traditional elements of Kodava identity, factors influencing the transition in identity, and its reflection in the contemporary period. 2024 Society for Research on Adolescence. -
The behaviour of macro and micro economic variables and the impact on systematic risk of non-banking finance companies
The reforms initiated by the Government of India during 1990s have brought fundamental changes in the structure and functioning of Banking and Non-Banking Institutions, their business models and the products and services offered by them. Global economic developments have altered the macro economic conditions of the respective nations and make the nations and their economies vulnerable to economic shocks in the form of systematic risk associated with their business activities. Macro-economic factors and micro economic factors have had effect on the risk level, assessing risk, measuring and managing risk has become paramount for Non-Banking financial Institutions. Individual influence of factors on the systematic risk as there is weak relationship with Beta but combined effect of factors is very positive on the systematic risk of the companies. Indian Institute of Finance. -
Initial public offerings and performance evaluation: Evidence from the Indian capital market /
International Journal of Economics And Financial Issues, Vol.8, Issue 5, pp.59-63, ISSN No:2146-4138. -
Markov analysis of unmanned cryogenic nitrogen plant with standby system
The unmanned cryogenic nitrogen plants operated by the industrial gas companies globally have their unique set of Reliability, Availability and Maintainability challenges. A generic reliability model of a typical unmanned cryogenic nitrogen plant is presented in this research work along with standby cryogenic storage System. The standby system is analysed for sensing and switching device as well as for load sharing system. The complexities of unmanned cryogenic nitrogen plant under repair with standby system are analysed using Markov method. A Markovian model has been developed for two different configurations: Configuration-1: Cryogenic nitrogen plant with gas and liquid production, nitrogen plant with only gas production and its dependence on the standby cryogenic storage system and to overall system reliability. Configuration-2: Considering cryogenic nitrogen plant is under repair and the standby system with external supply component under operation without failure and the system reliability of the configurations are solved by solving the set of differential equations and the solutions are presented in this paper. 2020 Author(s). -
Exploring the ethical implications of generative AI
Generative Artificial Intelligence (AI), an ever-evolving technology, holds immense promise across various industries, from healthcare to content generation. However, its rapid advancement has also given rise to profound ethical concerns. Illicit black-market industries exploit generative AI for counterfeit imagery, and in educational settings, biases and misinformation perpetuate. These issues underscore the need to grapple with the risks accompanying generative AI integration. Exploring the Ethical Implications of Generative AI emerges as a wellspring of insight for discerning academic scholars. It sets the stage by acknowledging generative AI's multifaceted potential and its capacity to reshape industries. The book addresses these complex ethical concerns, offering a comprehensive analysis and providing a roadmap for responsible AI development and usage. Its intended audience spans business leaders, policymakers, scholars, and individuals passionate about the ethical dimensions of AI. The book's objective is a twofold mission: to identify and dissect the ethical challenges inherent in generative AI while prescribing practical guidelines for its responsible development and utilization. By amalgamating the current research landscape, it aims to provide a comprehensive view of the field. Furthermore, the book introduces a set of practical guidelines that can serve as a guiding light for developers and users in diverse contexts, including workplaces, media, healthcare, education, and the military. By comprehensively addressing issues like bias, privacy, misuse, accountability, and responsibility, this book becomes the definitive guide for academic scholars navigating the ethical dilemmas of generative AI, ultimately safeguarding the responsible evolution of this groundbreaking technology. 2024 by IGI Global. All rights reserved. -
A Study on Emotion Identification from Music Lyrics
The widespread availability of digital music on the internet has led to the development of intelligent tools for browsing and searching for music databases. Music emotion recognition (MER) is gaining significant attention nowadays in the scientific community. Emotion Analysis in music lyrics is analyzing a piece of text and determining the meaning or thought behind the songs. The focus of the paper is on Emotion Recognition from music lyrics through text processing. The fundamental concepts in emotion analysis from music lyrics (text) are described. An overview of emotion models, music features, and data sets used in different studies is given. The features of ANEW, a widely used corpus in emotion analysis, are highlighted and related to the music emotion analysis. A comprehensive review of some of the prominent work in emotion analysis from music lyrics is also included. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
A Study of Emotion Classification of Music Lyrics using LSTM Networks
Emotion Recognition is a vital component of human-computer interaction and plays a pivotal role in applications such as sentiment analysis, virtual assistants, and affective computing. Long Short-Term Memory (LSTM) models are a subset of Recurrent Neural Networks (RNNs). It has gained significant popularity for their effectiveness in sequence modeling tasks, including emotion recognition. The study presents a review on the application of Long Short-Term Memory (LSTM) networks for emotion classification using music lyrics. It offers a thorough review of relevant literature and outlines the methodology for implementing LSTM models for emotion recognition. Furthermore, the study emphasizes the significance of hyperparameter tuning in building effective machine-learning models, particularly LSTM-based models. 2024 IEEE. -
Lightweight Anti DDoS Security Tool: Edge Level Filtering in SDN using P4
Software Defined Network (SDN) which has a promising future in satellite communication was first introduced as the solution to solve problems existing in the traditional network architecture. So far in SDN, mitigation strategies employed hardware installation or software solution which is heavily dependent on SDN controllers. The disadvantage of these approaches is the a) cost for implementation, b) intensive resource usage, and 3) costly optimization strategy necessary to enhance SDN performance. This research aims to fill the gap of the previously seen defense mechanism by enabling edge-level filtering without involving the control plane. By implementing filtering functions in edge switches, it can provide an efficient and effective defense layer in SDN network systems so that SDN switch can become the first line of defense against packet injection attacks. The proposed solution, Lightweight Anti-DDoS Software (LADS) focuses on lightweight workloads and provisioning of effective filtering mechanism to allow SDN switches to drop and block malicious packets sent by attackers. It utilizes Programming Protocol-independent Packet Processors (P4) programming language to create custom functionalities in SDN switches. P4 allows SDN switches to conduct host authentication and malicious packet filtering as well as blacklisting to isolate attackers. Simulation result proves that LADS efficiently manages malicious activities and maintains network performance during attacks at the data plane independent of SDN controller. 2023 IEEE. -
Getting Rid of Organizational Complacency in a Dynamic Environment
This case investigates the external consultants organizational diagnosis aimed at understanding the imperative for change within Infotics Solutions. It explores various concepts, including the nature of planned change and the resistance exhibited by employees. Emphasis is placed on the necessity of a comprehensive organizational diagnosis before embarking on the change process, highlighting the pitfalls of relying solely on a leaders intuition and experience to initiate change. Furthermore, the case underlines the implementation of human resource management interventions and their significance from both employee and organizational standpoints. It addresses the protagonists recognition of the need for external consultants expertise to grasp the problem and devise a strategic change process. The consultants methodical approach to planning change across different themes to achieve organizational objectives is elucidated, featuring the importance of employing the right diagnosis technique in situations where the problem is unclear. The case also showcases the consultants analytical approach to problem-solving, offering specific solutions tailored to the organizations needs. Ultimately, it illustrates the challenges faced by organizations that lean heavily on past successes and struggle to adapt to evolving environmental demands. Lastly, the case highlights the importance of analysing survey results and implementing theme-based interventions to address the issues confronting the organization and its employees at Infotics Solutions. 2024 Lahore University of Management Sciences. -
Frontline medical professionals in distress - Doctor heal thyself
Covid has changed our lives in many ways. People are scared to even step out of their houses, but health care workers have no option but to continue to work and care for the sick. Health care workers play a vital role in providing care to the infected persons, working beyond their capacities and risking their own lives. There is a lot of stress involved in the medical profession, and the pandemic made it worse. Each frontline health worker is at risk of getting infected with Covid during work and carrying it to their families, causing a lot of anxiety and mental health issues among the health care workers. According to a recent by the US Centers for Disease Control and Prevention (CDC), more than half of public health workers have reported symptoms of at least one mental health condition like depression, anxiety, and post-traumatic stress disorder (PTSD) in the recent past. A recent study among 422 doctors revealed 63.5% symptoms of depression, and 45% symptoms of stress, among frontline COVID-19 doctors. Physicians who perceived organizational problems related to procedural and informational justice were exposed to high levels of occupational stress. Every physician should have a personal doctor, and he or she has to seek suitable help as needed. The health care workers' stress is mainly associated with work stress as they are expected to work on a war footing and get very little time to spend with their families. There is a need to set up good psychiatric care for the medical professionals in the hospitals. The administrators of the hospitals should frequently check on the health and well-being of their employees. This article attempts to provide strategies to hospital administrators to help medical professionals reduce their stress levels. 2022