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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. -
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. -
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. -
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 -
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 -
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. -
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. -
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. -
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. -
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. -
Uncovering the sustainability reporting: bibliometric analysis and future research directions
In the past two decades, corporate sustainability reporting has witnessed tremendous growth and garnered a lot of attention among scholars, and practitioners around the world. It is no longer a matter of choice for companies due to immense pressure from various stakeholders to adopt sustainability practices. This article aims to analyze key research themes in Sustainability Reporting and its disclosure from 2002 to 2022, assess their impact, track field evolution, and identify emerging areas for future study. The data have been collected from the SCOPUS database using relevant keywords and utilized VOSviewer and Biblioshiny tools for bibliometric analysis, including citation trends, authorship patterns, and keyword frequency. This study reveals a surge in scholarly literature since 2012, with prominent clusters in sustainable development, sustainability, decision-making, and stakeholder engagement. CSR emerges as the dominant keyword. This study presents a comprehensive evaluation of existing scholarly work in the field of sustainability reporting, highlights emerging trends, and suggests future research directions in corporate sustainability. It also provides practical implications for organizations, policymakers, and stakeholders, bridging the theorypractice gap and enhancing researchs practical value. The Author(s), under exclusive licence to Springer Nature Limited 2023. -
A bibliometric analysis of sustainability and organizations performance
The incorporation of sustainability into an organizations performance is becoming an emerging topic to work upon. Moreover, conventional economic systems have had significant negative consequences for sustainable management, as well as imbalanced wealth distribution, which has resulted in natural catastrophes and population disparity. Sustainability practices in the current environment represent better quality performances and affect organizations performance. This research highlights the key areas and current evolution in the notion of sustainable development and organizational performance, as well as recommendations for further studies. Using the bibliometric analysis we examine a sample of 1442 articles published in Scopus between 1994 till 2021. The researcher identifies prominent authors, publications, and journals by employing a variety of network analysis techniques such as term co-occurrence, co-citation, and bibliography coupling with the help of VOS viewer. To the best of the authors knowledge, no other study has examined bibliographic data on sustainability and organizations performance; hence, this research is a one-of-a-kind addition to the literature. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
A Novel Approach to Predicting the Risk of Illegal Activity and Evaluating Law Enforcement Using WideDeep SGRU Model
The main reaction to the illicit extraction of natural resources in protected areas around the world is law enforcement patrols headed by rangers. On the other hand, research on patrols' efficacy in reducing criminal behavior is lacking. Similarly, tactics to enhance the effectiveness of patrol organization and monitoring have received very little attention. Sequencing is crucial for model training, feature selection, and preprocessing. Preprocessing steps include cleaning, discretizing, duplicating, and normalizing data. Feature selection makes use of genetic algorithms, which are basically search algorithms with an evolutionary bent that factor in natural selection and genetics. Training stacked GRU models necessitates meticulous feature management. Even the most cutting-edge algorithms, GRU and BiGRU, are no match for the suggested technique. An astounding 97.24% accuracy grade was disclosed by the results, showcasing exceptional growth. 2024 IEEE. -
Adoption of Sustainable Digital Technologies in Industry 4.0
We are living in a society that has been engulfed with growing technology, and the integration of it has become such an important part of our lives that it is scary to think of our daily lives without mobile phones, internet, or smart gadgets. Industry 4.0, briefly, means using new age technologies such as cloud computing, artificial intelligence, machine learning, Internet of Things, and big data in the different real-world applications of manufacturing, processing, and distribution of goods and services. Industry 4.0 involves making use of smart factories and technologies to minimize waste and to gain an absolute advantage in the development process. We already know the different use cases of these technologies and how these things help in lessening our workload, so it seems logical to apply them to broader aspects of our daily lives. Technologies mitigate our workload and improve efficiency. We have seen that these technologies are proving useful in different spheres of economics, with the help of new decision-making processes, model predictions, and even to improve healthcare. Through the scope of this chapter, we would shed light on how these different technologies are being incorporated and how these would help in stabilizing industry by its constant integration. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa. -
Blockchain Using Wireless Technology
In today's dynamic digital landscape, blockchain technology emerges as a pioneering force with the potential to redefine industries and transform the way we conduct business, share information, and establish trust. This chapter explores the foundational concepts of blockchain technology, its versatile applications, and the profound impacts it can have on various sectors. While blockchain holds immense promise, challenges like scalability, energy consumption, and regulatory frameworks must be addressed. Decentralized apps and smart contracts introduce new vulnerabilities that demand vigilant management. The integration of blockchain with wireless technology expands opportunities and streamlines processes. Wireless connectivity enhances accessibility, reach, and interaction with blockchain applications, benefiting finance, supply chain, and healthcare sectors. Real-time data sharing and reduced infrastructure reliance boost productivity. Environmental concerns, including blockchain's energy consumption and e-waste from wireless devices, need mitigation. In conclusion, the fusion of blockchain and wireless technology offers tremendous potential but demands a delicate balance between technological progress and environmental stewardship. Addressing reliability, security, scalability, and environmental impacts through innovative solutions and ethical practices is vital for a connected and sustainable future. 2024 CRC Press. -
Symbiotic cyanobacteria in gymnosperms
Cyanobacteria are a widespread group of phototrophic bacteria that are morphologically diverse and present on almost every environment on earth. Many cyanobacteria are able to fix atmospheric nitrogen and thus are able to form symbiotic association with a wide range of eukaryotic hosts such as plants, fungi, sponges, and protists. Cyanobacteria are able to provide carbon to nonphotosynthetic hosts such as fungi, but their primary role is to supply fixed nitrogen to enable the host to flourish in nitrogen poor environments. In turn, cyanobionts get the benefits of protection from competition, predation, and environmental extremes. Of all the cyanobacterial symbiotic associations, this chapter focuses on understanding the symbiotic association between gymnosperm and cyanobacteria. Species belonging to phylum cycadophyta are associated with nitrogen-fixing cyanobacteria (Nostoc species) through small specialized roots called coralloid roots. The cyanobionts are expected to have a heterotrophic mode of carbon nutrition, due to their location in coralloid roots (complete darkness). 2023 Elsevier Inc. All rights reserved. -
Encryption of motion vector based compressed video data
Enormous size of video data for natural scene and objects is a burden, threat for practical applications and thus there is a strong requirement of compression and encryption of video data. The proposed encryption technique considers motion vector components of the compressed video data and conceals them for their protection. Since the motion vectors exhibit redundancies, further reduction of these redundancies are removed through run-length coding prior to the application of encryption operation. For this, the motion vectors are represented in terms of ordered pair (val, run) corresponding to the motion components along the row and column dimensions, where val represents value of the motion vector while run represents the length of repetition of val. However, an adjustment for having maximal run is made by merging the smaller run value. Eventually we encrypted the val components using knapsack algorithm before sending them to the receiver. The method has been formulated, implemented and executed on real video data. The proposed method has also been evaluated on the basis of some performance measures namely PSNR, MSE, SSIM and the results are found to be satisfactory. Springer International Publishing Switzerland 2016. -
A hybrid scheme of image compression employing wavelets and 2D-PCA
In this paper, we have presented a method of compressing 2D grey-scale images employing wavelets and two-dimensional principal component analysis (2D-PCA). Principal component analysis (PCA) is an already established technique for image compression which primarily aims at exploiting inter pixel redundancies present in the image, while wavelet is a tool widely used in multi-resolution image processing. In the proposed method the image is subjected to a multi-resolution decomposition using wavelet. Subsequently, 2D-PCA is applied on the set of detail images at each level of resolution. The compressed form of the image is constituted by representative pairs of principal components and projection vectors from each level of resolution along with the approximate image at the coarsest resolution. The proposed method requires relatively few number of principal components (of varied dimension) to produce improved compression ratio with acceptable peak signal to noise ratio (PSNR). The method has been implemented and tested on a set of real 2D grey-scale images and the results have been assessed on both qualitative and quantitative basis by measuring parameters like compression ratio (CR), PSNR, structural similarity index measurement (SSIM) and the overall performance is found to be satisfactory. Copyright 2017 Inderscience Enterprises Ltd. -
A New Facile Ultrasound-Assisted Magnetic Nano-[CoFe2O4]-Catalyzed One-Pot Synthesis of Pyrano[2,3-c]pyrazoles
Pyrano[2,3-c]pyrazole derivatives have been synthesized through a one-pot multicomponent condensation of various 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 recovered using an external magnet and used repeatedly. 2019, Pleiades Publishing, Ltd. -
[18-C-6H3O+]: an in-situ generated macrocyclic complex and an efficient, novel catalyst for synthesis of pyrano[2,3-c]pyrazole derivatives
Synthesis of small aromatic heterocycles is of greater importance in the organic chemistry due to their vibrant applications in pharmaceuticals, agrochemicals and veterinary products. Pyranopyrazoles are one such class of heterocycles associated with numerous applications. Hence herein we report a multicomponent crown ether catalyzed, ultrasound irradiated methodology to make different functionalized pyranopyrazoles in a single step. This technique involves the in-situ generation of [18-C-6H3O+][OH?] complex, which in turn activates the aromatic aldehyde and aids in the facile nucleophilic addition. 2020, The Author(s).