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Sustainability disclosure and green finance: Driving the transition towards a sustainable future
In recent times, policymakers and scholars have directed their attention toward the notion of sustainability and green finance, coinciding with the growing global emphasis on environmental protection, climate change mitigation, and sustainable development. The integration of sustainability and green finance practices has emerged as a crucial strategy to address climate change, advance sustainable development goals issues, and build a resilient global economy in the face of pressing environmental challenges. The adoption of green finance and sustainability practices is no longer limited to developed economies. Many developing and under-developed countries are also taking a proactive approach to develop and implement a roadmap and framework for incorporating sustainability. In this chapter, the authors explore the notion of green finance, its crucial role in advancing sustainability, and the substantial consequences it can bring about for diverse businesses and stakeholders. 2023, IGI Global. All rights reserved. -
Carbon Disclosure and Organization Performance: A Literature Review
As a response to the threat of climate change, a growing number of businesses are voluntarily reporting carbon statistics. This article provides a comprehensive understanding of carbon disclosure, organization performance (OP), and cost of capital. This study aims to map the landscape of existing carbon disclosure and firm performance research completed over the past 10 years (2013-2022) utilizing bibliometric analysis. Sparked by the growing political, social, academic, and practical significance of controlling and reporting on climate-related concerns worldwide, this study analyzes the production and acquisition of information about significant regions and territories, institutions, publications, and channels for carbon disclosure and firm performance research using data from 878 publications retrieved from the Scopus database. To identify themes and subthemes in the research on carbon disclosure and firm performance, network analysis was utilized to reveal connections between the topics represented by keywords. Further, critical gaps have been highlighted in the literature, such as: the lack of carbon disclosure research across cross-sector settings, the lack of sectorial comparisons on the carbon disclosure practices, and the dearth of analyses of both pre-carbon disclosure and after-carbon disclosure practices and their impact on various financial and nonfinancial issues (for example, cost of capital and firm performance, sustainability, and climate change). Finally, this study makes specific recommendations for future carbon disclosure and firm performance research. 2023 Mary Ann Liebert, Inc., publishers. -
Optimization in the Flow of Scientific Newspapers
The evolutions that occurred in the past decades have provoked variations in the market as well as academic and research. Given this scenario, the research explored in this article was aimed to analyze the contribution of the management of PMBOK methods for the optimization of Scientific Editorial Flow. The methodology used presented a quantitative approach, of descriptive character based on a survey, made available on social networks and Facebook groups, through the google forms platform. The sample is given by Snowball, this type of sampling enables the researcher to study specific groups and is difficult to reach. The analysis was by descriptive statistics, using the Likert scale, as well as the weighted average and fashion responses. It was identified that the Critical Success Factors of a Project that can contribute to the optimization of the editorial flow of a Scientific Periodical are efficient communication, empowerment, change management, client involvement, supplier involvement and conflict management. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Exploring the Opportunities of AI Integral with DL and ML Models in Financial and Accounting Systems
With the integration of artificial intelligence (AI), today's fast financial landscape increasingly promises the most efficient and accurate processes for decision-making in accounting practices. On the other hand, the opacity of models represents a truly difficult challenge, given that transparency and accountability are key for using AI in making financial decisions. This is a research paper that focuses on the explanation of an XAI model application as a way of improving transparency in financial decision-making within the accounting field. The paper begins by outlining how transparency is important and opens the room for trust and understanding in the process of financial decision-making. Traditional black-box AI models, although able to provide remarkable predictions, usually exhibit low interpretability; this entails that stakeholders may have a small degree of understanding regarding the rationale behind the decisions. This provides a cloudy appearance not to hamper trust and supports compliance with regulatory standards like GAAP (Generally Accepted Accounting Principles) and IFRS (International Financial Reporting Standards). The proposed work applies to the accounting domain and brings about some of the different XAI techniques that are designed under this domain. The following techniques aim at demystifying the AI algorithms for effective AI stakeholders' understanding of the model predictions and underlying decision-making processes. 2024 IEEE. -
Brain Tumor Prediction Using CNN Architecture and Augmentation Techniques: Analytical Results
The brain, a complex organ central to human functioning, is susceptible to the development of abnormal cell growth leading to a condition known as brain cancer. This devastating disease poses unique challenges due to the intricate nature of brain tissue, making accurate and timely diagnosis critical for effective treatment. This research explores automated brain tumor prediction through Convolutional Neural Networks (CNNs) and augmentation techniques. Utilizing a task reused learning approach with the help of VGG-16, Mobile-Net and Xception architecture, the proposed model achieves exceptional accuracy (99.54%, 99.72%) and robust metrics. This Research explores the Augmentation techniques to enhance the precision and accuracy of the model used. The study surveys related models, emphasizing advancements in automated brain tumor classification. Results demonstrate the efficacy of the model, showcasing its potential for real-world applications in medical image analysis. Future directions involve dataset expansion, alternative architectures, and incorporating explanation techniques. This research contributes to the evolving landscape of artificial intelligence in healthcare, offering a promising avenue for accurate and efficient brain tumor diagnosis. 2024 IEEE. -
Single-use Plastic Packaging and Food and Beverage industry's take on it
Micro-plastics created by the gradual breakdown of SUP in oceans have recently been consumed by marine organisms, including fish, shellfish, etc. It is causing significant disturbance to marine life. The environment is littered with food packing. Snack food packaging is a great example of a long-standing, aesthetically obnoxious form of pollution. The majority of SUPs, especially perishable products, wind up in landfills within months of purchase.This is due to a rise in on-the-go food and beverage consumption, fueling the proliferation of single-use plastic packaging. The lack of dumpsters in some areas might contribute to an increase in littering. While the majority of food packaging plastics end up in the trash, municipal waste, landfills, and even the seas, a tiny fraction can be recycled. The reason for this is that poor countries have a prevalent culture of human waste. The Electrochemical Society -
Nonlinear radiation and cross-diffusion effects on the micropolar nanoliquid flow past a stretching sheet with an exponential heat source
Metallurgy, polymer and processing engineering, and petrochemical enterprises frequently encounter polar nanoliquid flows due to stretchable surfaces with radiative heat energy. Therefore, the radiative flow of a polar nanoliquid over a stretchable sheet is analyzed considering cross-diffusion and magnetic heat flux effects. The heat transport phenomenon is explored, including the characteristics of nonlinear radiation and exponential space-based heat generation. The highly nonlinear governing equations are converted to ordinary differential equations using apt transformations. These are, in turn, solved employing the finite difference method. The behavior of contributing parameters is presented using graphical visualizations. The interactive impacts of the pertinent constraints on the rate of heat transfer and skin friction are analyzed using three-dimensional surface plots. The enhancement of the temperature profile is observed by incrementing the radiation and exponential heat generation parameters. The magnetic field can be used to regulate the fluid flow as it decreases the flow field. Also, the heat generation factor has a predominant decreasing effect on the Nusselt number. 2020 Wiley Periodicals LLC -
Evaluating Energy Consumption Patterns in a Smart Grid with Data Analytics Models
With the rapid pace of technological advancement, it is a well established fact that in todays era, economical and industrial development go hand in hand with the growth in technology. Today, massive amounts of data are generated everyday and are only growing exponentially. The collected data, whether structured or unstructured, could prove to be very beneficial in terms of improving operational efficiency by analyzing and extracting valuable information to find patterns to optimize asset utilization and improve asset intelligence. Big data analytics can very well contribute to the evolution of the digital electrical power industry. The objective of this paper is to explore how smart grid technology can be enhanced by leveraging big data analytics. Different predictive models are used for the purpose. Among them, decision tree model outperformed others recording a training and tetsing accuracy of 94.4% and 92.7% respectively while noting a least execution latency of only 4.3 seconds. 2023 IEEE. -
Comparative Analysis of Digital Business Models
This paper discusses the comparative analysis of different attributes of Google and Facebook business model and their novel features for handling innovative business framework. We have compared Google and Facebook business model on different key attributes and also discussed the statistical analysis of business models using Google business analytics platform. We have argued performance analysis of these models. One important point which we discuss and analyze in this paper is that a business model is not about just building revenue generating machine, but it is indeed more than that. It explores the strategy and business approaches of both the models of revenue generating line of attacks. Our research contributes a considerate understanding of Google and Facebook architectural model and its influence on business framework. Statistical enactment and results are analyzed, precisely when big data and media are applied. This paper also provides better understanding of the digital marketplace for both of the platforms and its earning methodology. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
E-Commerce data analytics using web scraping
Some companies, like Twitter and others, provide an application programming interface (API) to fetch the information. If the API is not available, we will have to search other websites to get the data in a structured format. The primary way to get data from a web page is through web scraping. The basic idea of web scraping is to pull data from a website and convert it into a format that can be used for analysis. In this paper, we will discuss the simple explanation of how we can use Beautiful Soup to scratch data into Python and later save the extracted data in an Excel spreadsheet and do the spreadsheet analysis later. We will pull data from the Flipkart website to know the cell phone name, cell phone price, cell phone rating, and cell phone specification. 2023 Scrivener Publishing LLC. -
Predictive analysis of stock prices through scikit-learn: Machine learning in python
Scikit-learn, a tool for developing machine learning algorithms, is a standard library of python. Through Scikit-learn, a trained model for predictive analysis can be developed. Such models aim to provide accurate predictions. Stock predictions are based on changes and patterns identified in the historical dataset. Following the trends and patterns of the historical changes of stocks, machine learning algorithms can be developed for achieving accurate outcomes. An effective model is developed, which enhance the working pattern or performance of the machine that further helps to draw a precise analysis of stocks. 2023 Scrivener Publishing LLC. -
Implementation of tokenization in natural language processing using NLTK module of python
With the advancement of technologies, now it is possible to analyze the large amount of unstructured text circulated online with various tools and methods for understanding the changes as well to infer meaningful insights from the text data. In this work, the aim is to understand how Python can be used for text analytics by the help of various libraries available in it. The natural language processing (NLP) is being used to analyze and synthesize natural language and speech in Python. 2023 Scrivener Publishing LLC. -
Performance analysis and interpretation using data visualization
The matrix plot library (Matplotlib) is a unique feature in python that helps in the visualization of data via entering certain dataset and codes. It is a portable two-dimension of plot and images are mainly focused on visualizing scientific, technical, and financial data. These matrix plots are performing with the help of python programming and various user interface applications. Most familiar versions of joint photographic and supportable picture graphics are used for the picture visualization. These additional features include the various navigation processes, pages with the line, as well as images. The financial charts of open source website are used for tables and mathematical texts. The library is based on numerical python arrays, giving us visual access to massive quantities of data in readily consumable graphics. The problem statement here delves further into the functions of this feature, which will aid in a better understanding of Python's involvement in the data visualization. 2023 Scrivener Publishing LLC. -
Dealing with missing values in a relation dataset using the DROPNA function in python
Python provides a rich data structure library called PANDAS, which provides fast and efficient data transformation and analysis. The word PANDAS is an abbreviation of Python Data Analysis Library. PANDAS facilitate optimized and dynamic data structure designs work with "relational" or "labeled" data. Python's approach is meant to provide a high-level, high-performance building block that can be used to do real-world analysis of data. PANDAS Library is allowing users to import data from different file formats, such as CSV, SQL, Microsoft Excel etc. [1]. It helps in data preparation, as well as in data modeling, for those projects, which aims data analysis for the extraction of information. Python's future will be built on this layer for statistical computing. In addition to discussing future areas of work and growth opportunities for statistics and data analytics applications built on Python, the study provides details about the language's design and features [2]. In this research paper, we intend to solve the problem of missing values in a dataset using the DROPNA function in Python using PANDAS library. 2023 Scrivener Publishing LLC. -
A smart attendance system and method for permission inventory during the class /
Patent Number: 202111060922, Applicant: Shivani Chaudhry.
A smart attendance system (1). The system (1) comprises a smart lecture stand (2), which having an electronic unit (2A) which is connected to the other smart door, smart bench, and smart chair of the system; a smart bench (3), which having an electronic unit (3A), which is connected to the other smart door, smart stand, and smart chair of the system; a smart chair (4) comprises which having an electronic unit (4A); which is connected to the other smart door, smart bench, and smart stand of the system; a smart door (5) comprises a electronic unit (5A), which is connected to the other smart door, smart bench, and smart chair of the system. -
Multi-component condesation mediated synthesis of bioactive heterocyclic compounds
Aromatic heterocycles constitute the most diverse family of organic compounds. Moreover, aromatic heterocycles are widely used for the synthesis of dyes and polymeric materials of high value. The development of selective reactions that utilize easily available and abundant precursors for the efficient synthesis of heterocyclic compounds is a long-standing goal of chemical research. Despite the centrality of its role in a number of important research areas, including medicinal chemistry, total synthesis, and materials science, a general, selective, step-economical, and step-efficient synthesis of heterocycles is still needed. newlinePyrano[2,3-c]pyrazole derivatives have been synthesised by a one-pot multicomponent condensation of different aldehydes, dialdehydes, and ketones with malononitrile, ethyl acetoacetate, hydrazine hydrate (or phenylhydrazine) in the presence of magnetic nano-[CoFe2O4] catalyst under ultrasonic irradiation. The catalyst can be retrieved using an external magnet and used repeatedly. A practical, scalable method for obtaining various pyranopyrazoles has been demonstrated. The extraordinary catalytic role of the various catalyst has been discovered in the processes, which reveals a possible character of enhancing reaction rates and stabilising the intermediates during the course of the reactions. -
Impact of pharmacy industries growth on India economy during covid 19 /
Patent Number: 202241050891, Applicant: Deepha V.
Impact of Pharmacy Industries growth on India Economy during COVID 19 Abstract Pharmacy is an industry that can continue to function without being affected by economic fluctuations. This industry is socially respected by people. Whether people have food to eat or not, everyone wants to preserve the health of the body. In particular, the demand for medicines is more than ever in today's era. -
Inhibitory potential of ferula assafoetida extract on L-type calcium channel protein revealed by zebrafish studies and molecular docking
Ferula assafoetida is a part of many herbal formulations and hence it is pertinent to check the safety of its components specially to growing embryos. Zebrafish (Danio rerio) is considered to be one of the best models to study human embryonic development and metabolic pathways as its genome is fully sequenced and it possesses easily detectable developmental properties. In present study, the embryos of Danio rerio were treated with different concentrations of methanolic extract of Ferula assafoetida (MEFA) and its effects were checked at different post fertilization periods. Decreased heart beat rates, shrinkage of the chorion wall and other developmental abnormalities leading to the death of the embryos were observed. The methanolic extract of Ferula assafoetida was subjected to GC-MS to determine the different compounds present. Cardiotoxicity of these compounds were studied as it is one of the important factors for the retraction of a drug from the market. Molecular docking studies with L-type calcium channel (LTCC), a protein important for cardiac functioning, showed strong binding to the phytochemicals in the extract, with the maximum binding affinity observed with 26-hydroxycholesterol. The study proves that the methanolic extract of Ferula assafoetida contains phytochemicals which have the potential to cause cardiotoxicity in zebrafish embryos by interfering with the functions of LTCC possibly leading to arrhythmia. Altogether, our data suggest that the usage of these extracts in drug formulations should be done with caution. This is also indicative of the possible cytotoxic effect of the extract which could be tapped in the search for anticancer drugs. 2021 Chemical Publishing Co.. All rights reserved. -
Evaluation of web applications based on UX parameters
The objective of evaluating User Experience (UX) in this era of technology is to enhance the user satisfaction. Earlier applications were built with the aim of reducing the work of users. But with the evolution of the technology, the emergence of new gadgets and new trends in the information technology, the applications had to be more user-centric. The primary objective of this research is to evaluate the user experience of web applications based on different UX parameters using different techniques and given a rating. Each of these ratings are combined to determine the overall rating of UX for the web application. Also, the secondary objective of this research is to provide suggestions or recommendations based on the ratings to improve the UX of the web applications. An experimental study was conducted and the results show a significant improvement. Areas of further enhancements have also been identified and presented. 2019 Institute of Advanced Engineering and Science. -
Analysis of students' preferences for teachers based on performance attributes in higher education
Faculty evaluation is widely used not only for the appraisal of their performance, but also for curriculum innovation and development. There are many techniques to perform faculty evaluation. But these techniques do not address all the factors essential for evaluating a faculty. These evaluations are subjective in nature and found to be controversial as students' expectations vary. This hinders the main motive of faculty evaluation. To overcome this problem, there is a need to identify a suitable method to perform faculty evaluation. In this paper, the Conjoint Analysis, a mathematical statistics technique is used to analyze the major aspects that the students are expecting from their faculty. This technique increases the fairness in the appraisal process so that teaching can be made fun and effective. This research is a novel attempt that applies conjoint analysis to identify the major aspects of teaching in students' perspective. The proposed idea can be adapted to any domain where the customers' choice is valued particularly in Cloud computing services. 2019 Mithula G P, Arokia Paul Rajan R.