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Stock Price Prediction using Deep Learning and FLASK
The forecasting of stock prices is one of the most explored issues, and it attracts the attention of both academics and business professionals. It is quite difficult to make predictions about the stock market, and it takes extensive research into the patterns of data. With the expansion of the internet and indeed the growth of social media, online media and opinions frequently mirror investor sentiment. The volatility and non-linear structure of the financial stock markets makes accurate forecasting difficult. One of the sophisticated analysis techniques that is being used by academics in a variety of fields is the neural network. In this paper, we proposed deep learning techniques for google stock price prediction. A dataset from Kaggle was collected and applied deep learning techniques RNN, LSTM variants. We achieved better results with Bidirectional LSTM. We also created a web app for stock prediction using Christ University python FLASK. 2022 IEEE. -
Stock Price Prediction Using RNNs: A Comparative Analysis of RNN, LSTM, GRU, and BiRNN
Stock price prediction is a crucial area of financial market research, having significant implications for investors, traders, and analysts. However, given the dynamic and intricate nature of financial markets - which are impacted by a wide range of variables such as economic statistics, geopolitical developments, and market sentiment - accurately projecting stock prices is intrinsically difficult. Conventional techniques frequently fail to fully capture these dynamics, producing predictions that are not ideal. Recurrent Neural Networks (RNNs), one of the most recent developments in machine learning, provide potential methods to overcome these obstacles. Despite their potential, the effectiveness of different RNN architectures in stock price prediction remains an area of active research. This study compares four Recurrent Neural Network (RNN) architectures - Simple RNN, Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bidirectional Recurrent Neural Network (BiRNN) - for forecasting the Nifty 50 index values on the Indian National Stock Exchange (NSE) from the year 2000 to 2021. Using a comprehensive dataset spanning two decades, we assess each model's performance using the metrics Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The data shows that the BiRNN model regularly outperforms the other models in all criteria i.e., MAE, MAPE, and MSE, indicating higher predictive accuracy. This study adds to the existing research by offering useful insights into the usefulness of RNN models, especially that of the BiRNN model for predicting stock prices, specifically in the setting of the Nifty 50 index. Our findings emphasize BiRNN's potential as a stock price prediction model and open new options for future research in this area. 2024 IEEE. -
Stocks and throughput Accounting on Material Management and its Impact on Cost Management
Global Journal of Arts and Management, Vol. 2, No. 3, pp. 244-246, ISSN No. 2249-2658 -
Stormy minds and the long-term mental health impact of climate-linked natural disasters
This chapter delves into the enduring psychological ramifications stemming from climate-linked natural disasters, encapsulated in the term "Stormy Minds." As our planet grapples with an escalating frequency of such events, understanding the protracted effects on mental health becomes imperative. This abstract provides an insightful overview of the research, focusing on the intricate interplay between climate-induced disasters and the long-term well-being of individuals. Drawing on interdisciplinary perspectives, the study explores the psychological dimensions of enduring stress, anxiety, and trauma caused by these disasters. By assessing and documenting the persistent mental health impact, the research aims to contribute valuable insights for policymakers, mental health professionals, and communities striving to build resilience in the face of an increasingly turbulent climate. 2024, IGI Global. All rights reserved. -
storytelling a transformative technique
Complex philosophical and ethical teachings are often conveyed through parables and fables, ensuring that wisdom is passed down through generations, writes John J Kennedy -
Storytelling: An effective way of advertisement /
When the word advertisement strikes the minds of the audience, the very first thing they tend to do is either change the channel or skip it. The term advertisement has always been as something that is only meant to promote a product or a service. Until the last few years, have always seen advertisement as just an Integrated Marketing Communication. Storytelling form of advertisement is not something we see very often on TV or on the Internet. -
Straightforward synthesis of mn3o4/zno/eu2o3-based ternary heterostructure nano-photocatalyst and its application for the photodegradation of methyl orange and methylene blue dyes
Zinc oxide-ternary heterostructure Mn3O4/ZnO/Eu2O3 nanocomposites were successfully prepared via waste curd as fuel by a facile one-pot combustion procedure. The fabricated heterostructures were characterized utilizing XRD, UVVisible, FT-IR, FE-SEM, HRTEM and EDX analysis. The photocatalytic degradation efficacy of the synthesized ternary nanocomposite was evaluated utilizing model organic pollutants of methylene blue (MB) and methyl orange (MO) in water as examples of cationic dyes and anionic dyes, respectively, under natural solar irradiation. The effect of various experimental factors, viz. the effect of a light source, catalyst dosage, irradiation time, pH of dye solution and dye concentration on the photodegradation activity, was systematically studied. The ternary Mn3O4/ZnO/Eu2O3 photocatalyst exhibited excellent MB and MO degradation activity of 98% and 96%, respectively, at 150 min under natural sunlight irradiation. Experiments further conclude that the fabricated nanocomposite exhibits pH-dependent photocatalytic efficacy, and for best results, concentrations of dye and catalysts have to be maintained in a specific range. The prepared photocatalysts are exemplary and could be employed for wastewater handling and several ecological applications. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Strain energy based frequency independent impedances of soil for interaction effect on structure
The present study proposes a strain energybased method for evaluating soilstructure interaction (SSI) effects for ground-mounted parabolic antenna systems founded on layered soils. Conventional frequency-independent impedance formulations, such as those recommended in ASCE 4-16, are primarily based on homogeneous soil assumptions and may not adequately capture the dynamic behavior of layered soil profiles. In this work, a strain energy equivalence approach is developed to estimate translational and rotational soil impedances by accounting for depth-wise variations in soil stiffness. The proposed method is validated using three-dimensional finite element modeling and in-situ microtremor measurements. The results demonstrate improved prediction of natural frequencies and modal mass participation factors compared to standard impedance-based approaches, indicating that the proposed method provides a more realistic representation of SSI effects for precision-sensitive antenna structures. 2026 Techno-Press, Ltd. -
Strain-Induced Tribocatalytic Activity of 2D ZnO Quantum Dots
The use of low-frequency vibration or high-frequency ultrasound waves to create polarization and an inherent electric field in piezo-tribocatalysts has recently been shown to be a novel advanced oxidation process. In this study, we have demonstrated the synthesis of two-dimensional (2D) ZnO quantum dots (QDs) and their strain-induced tribocatalytic effect, where the triboelectric charges generated under the influence of friction and strain are used to facilitate the decomposition of organic dye molecules. The catalytic performance of 2D QD catalysts can be tuned by modulation of the strain-induced band-gap variation, which are typically regarded as the active sites. The underlying mechanism for the strain-induced catalytic performance is due to the presence of defective dipole moments. Detailed theoretical investigations reveal strain-induced charge-transfer-dependent catalytic properties of the 2D ZnO QD-polymer interface. We believe that the present work provides a fundamental understanding of the design of high-performance catalysis applications for water cleaning and emerging technologies. 2024 American Chemical Society. -
Strain-induced wave energy harvesting using atomically thin chromiteen
Developing non-corrosive wave energy harvesters is one of the critical technologies required for sustainable energy harvesting. This work studies the effect of surface defects in atomically thin chromiteen for harvesting energy from water waves. An external strain further enhances the surface charge properties of the chromiteen, resulting in higher electrical output in the fabricated flexible nanogenerator (C-FNG) to harvest wave energy. The peak output voltage of the C-FNG device was ?5 V due to the water wave force. The density functional theory (DFT) results indicate the presence of surface defects in the 2D chromiteen, and the applied strain gradient introduced a redistribution of electron density, possibly due to altered bond lengths in the material. The present work provides an atomistic study of energy harvesting in the marine environment to provide power for deep-sea divers, ships, and any other small electronic sensors or marine Internet of Things in remote areas. This journal is The Royal Society of Chemistry, 2025 -
Strained Symbiosis: AIADMK, BJP, and the Shrinking Space for Dravidian Politics in Tamil Nadu
In Tamil Nadu, the electorate still listens keenly for ideological clarity. The question is: will the AIADMK find the courage to speak? -
Strategic competency development in indian tourism: Harnessing digital transformation, sustainability, and human capital
The Indian tourism sector is experiencing a significant transformation influenced by technology, sustainability, and changing consumer expectations. This chapter examines how competency marketing can enhance the industry's competitiveness, particularly in digital transformation, sustainability, and human capital development. Drawing on global tourism leaders, it highlights the use of digital tools like big data, AI, and ML to offer personalized experiences. The chapter underscores sustainability as a marketing competency and the importance of continuous professional development. It advocates for industry-academia partnerships and regional training programs to support mid-career professionals. India is poised to lead in digital tourism marketing by aligning competencies with emerging technologies and sustainability goals. Key performance indicators such as digital literacy and sustainable tourism engagement are proposed to guide the sector's growth over the next decade. 2025, IGI Global Scientific Publishing. All rights reserved. -
Strategic Data Analytics for Sustainable Competitive Advantage
Data and analytics have become major assets for all organizations to leverage into superior strategic positions in this cut-throat competitive world with buzzwords like data crunch, metrics, and dark data. This chapter discusses the structural and economic reasons of why business analytics is necessary for organizations. The ability to collect different resources and entities such as talent, process, data, and information technology to bring out a valuable output is crucial for business analytics success. The most common difficulty of big data begins when organizations are in the journey of business analytics. Since a number of organizations are still in the baby steps of basic, tackling data challenges is humongous for them. This situation calls for the need to foster a business analytics ecosystem by every organization. This paper discusses how optimizing analytics could lead to a sustainable competitive advantage, building data strategy, and setting Key Performance Indicators (KPI) for business analytics. The chapter further explores how analytics is used across business domains and the challenges in crafting a business analytics strategy. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Strategic Decision-Making in The Era of Artificial Intelligence: A Multi-Dimensional Evaluation of Opportunities, Challenges and Ethical Concerns
This paper explores the impacts of Artificial Intelligence (AI) on strategic business decisions, focusing on the opportunities, hurdles, and ethical aspects associated with embedded AI in organizations. With a mixed-methodology, the study does not rely solely upon quantitative data to assess decision-making consequences influenced by AI and machine technologies, but includes qualitative feedback from business leaders on the ground. The findings imply that while AI significantly enhances data analysis and informs strategic decisions, it also raises issues about transparency, accountability, and whether there may be bias embedded in decisions driven by algorithms. Nowhere is this more apparent than in the healthcare sector, the implications of which are significant as greater reliance on AI can facilitate improving operational efficiencies and patient results, but it also demands robust frameworks to confront the ethical issues around patient privacy and informed consent. Ultimately, this work fuels the debate regarding the transformative effect of AI on business strategy and highlights that the incorporation of ethical considerations cannot be compromised if we are to develop guidelines in this area. These recommendations can help to mitigate AI-related risks and enable responsible AI adoption in the healthcare and other contexts, and pave the way for future research on the emergent technology-strategic management connection. Neeraj Kumar et al. -
Strategic design of MXene/CoFe2O4/g-C3N4 electrode for high-energy asymmetric supercapacitors
MXenes are emerging as the next-generation materials for energy storage due to their substantial surface area, exceptional conductivity, and abundant surface-terminating groups. However, the tortuous path for ion transfer within the restacked layers significantly limits the electrochemical performance of multilayered MXenes. To overcome this, interlayer spacers have been introduced. These spacers help mitigate ion diffusion barriers and enhance the accessibility of active sites, thereby improving the overall efficiency and longevity of MXene-based supercapacitors and related devices. In this study, a rational material is designed by incorporating CoFe2O4 and g-C3N4 into the layers of MXene through ultrasonication for supercapacitor application. The physicochemical properties of the synthesized materials have been comprehensively characterized using diverse techniques, revealing that MXene/CoFe2O4/g-C3N4 has successfully evolved into a multilayered structure possessing enhanced surface area, low restacking tendency, high pore diameter, and excellent pore volume. Leveraging these properties, it performs as a viable material for fabricating the working electrode with a specific capacitance (Csp) of 1506.2 F g?1 at a current density of 5 A g?1 in 3 M KOH. It shows good stability with 89 % capacitance retention over 7000 cycles. An asymmetric supercapacitor (ASC) constructed with MXene/CoFe2O4/g-C3N4 as positive electrode and activated carbon as negative electrode exhibits an energy density of 79.8 Wh Kg?1 and power density of 1343.3 W Kg?1. Furthermore, it shows a capacitive retention of 91 % over 10,000 cycles. This MXene based composite, with excellent capacitance and outstanding stability, offers an appreciable performance in the field of sustainable energy storage. 2024 Elsevier B.V. -
Strategic framework to analyze critical success factors of marketing 4.0 operations: evidence from an emerging economy
Purpose This research study aims to develop a strategic framework that identifies, classifies and prioritizes the critical success factors (CSFs) essential for implementing Marketing 4.0 in emerging economies. It seeks to bridge the gap between theoretical discourse and operational realities in digitally transforming markets. Design/methodology/approach Following an elaborate review of the extant literature, 38 such CSFs emerged, which were then segmented using principal component analysis into seven relevant dimensions. The constructs were validated using confirmatory factor analysis (CFA). Thereafter, the fuzzy-decision-making trial and evaluation laboratory (DEMATEL) was used to map the cause-and-effect relationship among the reduced component factors. Findings The results demonstrate that digital marketing (S2), channel cohesiveness (S3), driving technologies (S5) and mutual value proposition (S7) are found to be cause factors, while customer engagement (S1), market dynamism (S4) and strategic marketing (S6) are identified as effect factors. Originality/value The novelty of this study is embedded in integrating multianalytical approaches like principal component analysis, CFA and Fuzzy-DEMATEL to empirically validate and rank the CSFs of Marketing 4.0. This study also extends the theoretical understanding of Marketing 4.0 by aligning critical enablers with the dynamics of emerging markets. 2026 Emerald Publishing Limited -
Strategic Innovation and Sustainable Customer-Centric Growth
Strategic innovation and sustainable customer-centric growth drive long-term success in today's evolving business landscape. Organizations that prioritize innovation adapt to changing market demands while ensuring they stay ahead. By placing the customer at the core of their strategies, businesses can create lasting value, build brand loyalty, and drive meaningful growth that balances profitability with long-term sustainability. This approach requires a continuous alignment of innovative efforts with customer needs, emerging technologies, and environmental and social responsibility. The convergence of strategy, innovation, and a customer-centric mindset may build resilient and future-ready organizations. Strategic Innovation and Sustainable Customer-Centric Growth explores how organizations can leverage strategic innovation to develop sustainable, customer-centric business models that drive long-term growth. It examines the integration of customer insights, technological advancements, and sustainability practices into core strategies to create competitive advantage and lasting value. This book covers topics such as business strategy, circular economics, and digital marketing, and is a useful resource for business owners, academicians, researchers, and scientists. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Strategic Integration of AI in Modern Data Management
The exponential growth of data from sources such as social media, IoT, and enterprise systems has catalyzed a transformative shift in data management practices. This paper explores the integration of artificial intelligence (AI), edge computing, cloud-native frameworks, and graph-based techniques to support intelligent, low-latency, and scalable data processing across complex ecosystems. It presents a comparative analysis of classical versus modern data architectures, highlighting how technologies like Graph Neural Networks (GNN4TS), reinforcement learning, and large language models (LLMs) enable more adaptive, interpretable, and automated pipelines. The study also addresses challenges in legacy system modernization, time-series modeling, and cyber threat detection while underscoring the role of AI in autonomous database management and metadata enrichment. Further, it examines critical risks - including explainability, adversarial vulnerabilities, concept drift, and privacy preservation - associated with AI-integrated data workflows. A structured overview of emerging paradigms such as neuro-symbolic AI, adaptive governance in multi-agent systems, and the potential of quantum computing provides a future-focused lens on intelligent data ecosystems. The insights presented aim to assist researchers, data engineers, and decision-makers in navigating the evolving landscape of AI-driven data management. 2025 IEEE. -
Strategic Integration of HR, Organizational Management, Big Data, IoT, and AI: A Comprehensive Framework for Future-Ready Enterprises
This exploration paper proposes a comprehensive frame aimed at fostering unborn-ready enterprises through the strategic integration of Human coffers(HR), Organizational Management, Big Data, the Internet of Things (IoT), and Artificial Intelligence(AI). By synthesizing these critical factors, the frame seeks to optimize organizational effectiveness, enhance decision-making processes, and acclimatize proactively to evolving request dynamics. Through a methodical review of being literature and empirical substantiation, the paper delineates the interconnectedness of these rudiments and elucidates their collaborative impact on organizational performance and dexterity. likewise, it explores perpetration strategies and implicit challenges associated with espousing such an intertwined approach. This paper not only contributes to the theoretical understanding of strategic operation but also provides practical perceptivity for directors and directors seeking to navigate the complications of the contemporary business geography and place their associations for sustained success in a decreasingly digitized and competitive terrain. 2024 IEEE. -
Strategic Management During a Pandemic
The COVID- 19 pandemic changed world dynamics, working scenarios, as well as professional and emotional dimensions. The virus has emerged as a significant threat for the continuity of business. Keeping the gravity of the problem in mind, companies must understand the need for change and must now update their strategy to account for pandemics. The next pandemic may be more severe than the current one, meaning that organizations need to devise mechanisms and business models to fight with these situations and maintain business continuity. They should not only look forward to saving plants, machinery and infrastructure, but also concentrate on employee welfare, customer engagement and satisfaction during this crisis time. The book will not only present the evidence of various effective solutions to run a business in the time of a pandemic, but also put forward the new models and practices of business being followed by people at the time of crisis. It aims to create a bridge between existing business models and proposed business solutions, focusing on existing theories and most importantly case studies from the recent happenings. This rich collection of chapters will provide insights regarding the business challenges, opportunities and practices during pandemic situations like COVID- 19, making it particularly valuable to researchers, academics and students in the fields of strategic management, leadership and disaster management. 2022 selection and editorial matter, Vikas Kumar and Gaurav Gupta.