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Predicting Stock Market Indexes with Artificial Intelligence
The forecasting of the Share market has been a popular research area, involving the analysis of input and output stock data using computer technology and algorithmic knowledge. This involves building unpredictable relationships among the data and analyzing the stock market trends to provide a reference for investors. The inception of artificial intelligence (AI) technology, blended with the web, immense data, and cloud computing has provided technical support for various industries. AI technology is employed to scrutinize and predict the equity market, exploring curvilinear associations amid stock market information, and furnishing a foundation for investors to formulate investment determinations. Predicting equity prices is a demanding undertaking due to diverse factors like governmental happenings, fiscal circumstances, business resolutions, investor mentality, and overseas currency hazards. The securities exchange is a vastly active and disordered framework, and producing precise projections of the securities exchange is of paramount significance. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Analyzing the Market Dynamics of Electrical Appliances with a Special Emphasis on Sustainable Electric Energy
This study looks into the market dynamics of electrical appliances with a special emphasis on sustainable electric energy. The research aims to understand how factors such as technological advancements, consumer behavior, and regulatory policies influence the electrical appliances market. By examining the trends and challenges within this sector, the study highlights the growing importance of sustainability in product development and consumer choices. The main areas of focus include the adoption of energy-efficient technologies, the impact of rising household incomes on appliance usage, and the role of government policies and initiatives in promoting sustainable energy consumption. The findings of the study would provide insights into how the industry can align its practices with environmental goals while meeting the evolving needs of consumers. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Multi-level Prediction of Financial Distress of Indian Companies Using Machine Learning
Predicting Financial Distress (FD) and shielding companies from reaching that stage is vital, even indispensable for every business. FD, if not attended to on time, ultimately leads to bankruptcy. Prediction variables are essential to forecast the wreckage in the business; however, the prediction is successful when suitable models are used. This study aims to predict FD at three levels: from mild to severe, by applying a machine learning algorithm. The study identifies modern models using the machine learning approach for predicting multi-level FD and summarises the significance of modern models through machine learning technology, to sustain the future development of the economy. The modern models are free from rigid assumptions and have proved to be the best in the prediction of FD. The results show that FD prediction is important at multiple stages. The models performance will be high when the best features are selected using the Pearson Correlation and SFS Feature selection approach. Among the ten models used in the study, LightGBM Classifier shows the highest performance of 80.43% accuracy without feature selection. However, with Pearson Correlation Approach and SFS Feature Selection methods, the accuracy is 82.68% and 86.95% respectively. This study has major implications for the stakeholders of the company to take timely decisions on their investment and for the management as a yardstick to check the performance of the business. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Traditional Ecological Knowledge Repository in the Indian Himalayas: An Overview
Traditional ecological knowledge (TEK) refers to a body of informa-tion that is also referred to as local knowledge, traditional knowledge, native knowledge, and indigenous technological knowledge. A number of studies show the role of traditional ecological knowledge in decision-making in social-ecological systems that support sustainability and resilience. International agencies have also highlighted and emphasised the importance of TEK practises in the preservation of biological variation. For instance, the UN Convention on Biodiversity, Article 8 (j), makes it very plain that respect, maintain, and promote innovation and practises of indigenous and aboriginal populations connected with sustainable use of biolog-ical diversity are essential. The benefits of TEK for sustainable forest management were acknowledged in the 2005 Millennium Ecosystem Assessment Report by the World Bank. As environmentalists, anthropologists, and arborists share interests in TEK for academic, social, or economic reasons, this highlights the significance of TEK in difficulties relating to biodiversity protection. Numerous components of TEK are seen favourably by experts in fields of forestry, irrigation, architecture, ethno-biology, irrigation, agriculture, medicine, sun and water conservation, conventional weather prediction, adaptation to climate change, and disaster risk reduction. Indian Himalayan Region (IHR) is predominantly populated by indigenous peoples and local societies, which are quite diverse in terms of socio-culture and race. The region has nearly 40% of all of Indias indigenous tribes. This area is also special for its tradi-tional ecological knowledge. Many of the TEK-based practices have supported local communities in earning a livelihood. The indigenous peoples expertise and expe-riences are said to play a crucial part in preventing climate change, and they may give important information on the implications of climate change. Hence, sustaining biodiversity in the IHR is also a means of defending indigenous peoples rights. By making the TEK the focal point of governance systems at the IHR, the variety of options for sustainable growth and even the co-production of the body of knowl-edge would be expanded. Therefore, it seems sensible to get knowledge from the TEK before it is lost to the onslaught of modernity. However, there are numerous problems or issues with traditional ecological knowledge in India, including igno-rance in considering conservation policies by the Indian government and the lack of effective documentation of this priceless knowledge. To develop sustainable and culturally suitable management techniques, it is currently a challenge to combine indigenous knowledge standards and management methods with Western science. Realising the above, this chapter attempts to comprehend the concept of TEK and its application throughout a variety of resource management contexts throughout a variety of resource management scenarios. Further, it will explore various issues and challenges and examine the regulations thereof. Lastly, this chapter concludes by highlighting the strategies and suggestions for an effective repository of traditional ecological knowledge in the Indian Himalayan Region. 2024 The Author(s). -
Innovation journey: Unleashed business applications framework
This chapter gives a thorough framework for understanding the dynamics and applications of innovation in the business environment. In today's fast-paced and competitive world, innovation is essential for organizational growth, adaptation, and sustainability. This study takes a descriptive approach, addressing the complexities of creativity across multiple dimensions. This chapter offers a conceptual overview before examining the various aspects of innovation and its function as a driving force behind strategic initiatives and a means of fostering competitive advantage. It provides a thorough study that clarifies the various stages of the innovation process, from ideation to optimization, emphasizing key challenges and opportunities at each level. It provides a road map for businesses looking to foster an innovative culture and use it as an outlet for value creation and competitive advantage by adopting a comprehensive viewpoint. 2024, IGI Global. -
Harmonizing human resource strategies navigating employer branding in sustainable organizations
In the framework of sustainable businesses, this chapter examines the synergies between employer branding and human resource (HR) strategies. In order to establish a harmonic organizational framework, this chapter thoroughly investigates how HR practices might be strategically aligned with sustainability goals. It explores the opportunities and challenges of managing employer branding within sustainable business practices. It sheds light on specific variables and practices that must be considered to develop an employer brand that reflects the organization's commitment to sustainability. In order to create an integrated, attractive, and socially responsible employer brand, it is important to align their human resources practices with sustainability initiatives. It provides insights into the strategic integration of employer branding and human resources, presenting a roadmap for businesses looking to match their HR procedures with sustainability programs. 2024, IGI Global. All rights reserved. -
Catchment-specific approaches in human resource management: Enhancing recruitment practices
In today's dynamic business outdoors, identifying the most skilled employees has become a challenging and captivating challenge. This chapter explores the catchment-specific approach in human resource management in the information technology (IT) industry. This conceptual chapter analyzed peer-reviewed academic literature, the business press, and other media outlets. This conceptual chapter outlines the key issues for catchment-specific approaches in human resource management in the area of recruitment with the changing trends of the recruitment process. Certain emergent practices include analyzing the catchment area, tailoring recruitment strategies, and evaluating and refining catchment-specific in recruitment. This chapter helps raise awareness and understanding of this new and emerging aspect of catchment-specific approach in human resource management. 2024, IGI Global. All rights reserved. -
Pilot Study on Adoption and Usage of AI in Food Processing Industry by UTAUT2
Artificial intelligence (AI) improves the efficiency of work and effectiveness in the output. Currently, food processing industries have started using AI in their business operations. It is crucial to have an in-depth understanding of the adoption and usage of AI systems in food processing industries. Therefore, this paper validates the Unified Theory of Acceptance and Use of Technology (UTAUT2) in the context of the food processing industry. This study applied AI to the food processing industries in the Bengaluru region. The study's objective is to build a clear vision of the factors that affect the user acceptance and behaviour intention of the user by pilot test. The pilot survey collected 62 responses through the questionnaire. The respondents were employees from the food processing industries in Bengaluru. The reliability test of the questionnaire was done by using Jamovi 2.3.16 software. The questionnaire was tested in three ways: Cronbach Alpha, McDonalds Omega, and Inter-rater reliability. The results of the entire test were reliable since overall Cronbach Alpha of 0.874, which is within the range of 0.800.90, and considered good internal consistency. Similarly, McDonalds Omega is within the range of 0.800.90, which is excellent consistency, and Inter-rater reliability is within the range of moderately acceptable scores from 50 to 75%. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Occupancy improvement in serviced apartments: Customer profiling
Sustaining and improving higher occupancy and generating steady revenue by bringing the experience of Home away from Homefor the Customers is the business model of ServicedApartments Industry. Serviced Apartment Industry has to be highly competitive. Its performance is governed by many factors such as competition, technology, social factors and lastly Customers themselves. This study focuses only on Customer profile. To achieve results, the Serviced Apartment Owners/Managers will need to study Customers profile and their needs. Customer satisfaction and retention lead to better customer loyalty, occupancy rates, and revenue. In this paper a methodological framework to analyze and profile Serviced Apartment Customers is discussed, focusing on the factors and particularly the Customer information which could help in increasing the Occupancy. There is a trend that would normally go unnoticed if analysis of data is taken at the aggregate level but looking at them individually, it provides interesting information. 2012 Taylor & Francis Group, London. -
Sustaining Sustainable: Investigating the Full Spectrum of Food Waste, from Production Through Consumption to Disposal
Purpose: The purpose of this research is to explore the primary factors that contribute to food waste. Additionally, it creates practical strategies to cope with food waste and encourages to perform sustainable practices to improve the environment. Additionally, the study presents an analytical framework for supply chain problems as well as the methods that are environmentally friendly. Methodology: The research begins by defining how sustainable development should be incorporated in the hospitality sector and by briefly outlining its attributes. Next, it discusses the expanding interest in supply chain management and outlines an overview of the breadth of academic research on sustainability in the literature related to the hotel industry. Findings: The paper examines the enormous ecological and economic effects of food waste, including how it contributes to the adverse global warming, the dwindling of natural resources, and also the loss of worthwhile financial investments. Additionally, it highlights the social effects of food wastage, such as how it contributes to gaps in access to nourishing foods and food insecurity. Research Limitations: It attempts to shed light on the scope of food loss, identify major contributing variables, and suggest methods to reduce food loss along the whole supply chain through an examination of current literature and data. Practical Implication: The practical application of this research is to offer evidence-based insights and practical recommendations to policymakers, organizations, and people with an aim to decrease food waste and enhance the effectiveness of the food system. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
IoT and wearables for detection of COVID-19 diagnosis using fusion-based feature extraction with multikernel extreme learning machine
Presently, wearables act as a vital part of healthcare sector and they are able to offer exclusive perceptions about the person's health conditions. In contrast to traditional diagnosis in a hospital environment, wearables can give unrestricted access to real-time physiological data. COVID-19 epidemic is increasing at a faster rate with limited test kits. Hence, it becomes essential to develop a novel COVID-19 diagnostic model. Numerous studies were based on the utilization of artificial intelligence techniques on radiological images to precisely identify the disease. This chapter presents an efficient fusion-based feature extraction with multikernel extreme learning machine (FFE-MKELM) for COVID-19 diagnosis using internet of things (IoT) and wearables. Primarily, the wearables and IoT are used to capture the radiological images of the patient. The presented FFE-MKELM model incorporates Gaussian filtering based preprocessing for removing the noise that exists in the radiological image. Besides, directional local extreme patterns with deep features based on Inception v4 model are applied for the FFE process. In addition, MKELM model is utilized as a classification model to determine the appropriate class label of the input radiological images. Moreover, monarch butterfly optimization algorithm is applied to fine tune the parameters involved in the MKELM model. Experimental validation of the FFE-MKELM model is performed against benchmark dataset and the outcomes are inspected under different measures. The resultant simulation outcome ensured the betterment of the FFE-MKELM method by demonstrating an increased sensitivity of 97.34%, specificity of 97.26%, accuracy of 97.14%, and F-measure of 97.01%. 2022 Elsevier Inc. All rights reserved. -
Perception of online adult education in different countries
Adult education has gained immense popularity during a pandemic. Adult learners are able to meet their educational requirements through online education. Adult learners also prefer online education due to convenience and self-learning interests. Online education also poses challenges and discomfort to online learners. Statistics indicate a higher dropout rate among adult online learners due to various factors. This chapter focuses on the significant challenges adult online learners face and has identified tools, strategies, and techniques to empower and motivate them. This chapter will also help us to understand how tools and techniques, such as information and communication technology, allow us to increase the number of such learners in different countries. Information and communication technology tools are used in developed and developing countries to encourage and motivate adult learners to improve their education virtually at their convenience. 2023, IGI Global. All rights reserved. -
Green Minds, Green Future: Impact of Environmental Education on Students Attitudes and Intentions
The objective of this research is to examine the effect of environmental education on green behavior mediated through environmental awareness, environmental attitude, and behavioral intentions, as mediating variables. The sample population comprised of the students of various universities of Delhi, National Capital Region (NCR), as this region of the country has the highest level of environmental pollution and therefore it is the most appropriate population for this study. One thousand questionnaires were shared among students of Delhi, NCR via Google Form out of which 689 responses were received and analyzed using structural equation modeling (SEM). The results exhibited the association between environmental education and green behavior which was significantly mediated by awareness, attitude, and behavioral intention. The findings of the study have implications for both research and practice. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Conclusion
[No abstract available] -
Role of international commercial arbitration in resolving WTO disputes
International organizations flourished with the fragrance of effective interactions between parties and reconciliatory measures promoting amicable dispute settlement. In this scenario International Commercial Arbitration comes to the rescue of international organizations resolving multilateral, bilateral, and investment disputes between the parties, promoting sustainable development. The rationale of the article is to promote the parties towards a system of dispute redressal that is opposite to adversarial form of dispute resolution and thereby promoting an arbitration-friendly economy. Arbitration is not considered to be a preferable dispute resolution and the article provides for importance of arbitration in research gap in various research papers by using doctrinal research, analyzing articles and statutes, and providing an answer to the research question "How to promote sustainable development through International Commercial arbitration" and "How to promote arbitration-friendly environment. " This article discusses WTO dispute resolution board's novel approach to promoting arbitration. 2024 Srinesh Thakur, Anvita Electronics, 16-11-762, Vijetha Golden Empire, Hyderabad. -
Intelligent Manufacturing Components, Challenges, and Opportunities
Intelligent Manufacturing shows transformative paradigms in the manufacturing industry; leveraging advanced technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and robotics, to develop highly automated and adaptive production systems. This chapter outlines the Intelligent Manufacturing process, including its key principles, components, challenges, and opportunities. The combination of Machine Learning (ML) techniques and AI enables decision-making, real-time optimisation, and predictive analytics of manufacturing processes, productivity, and quality of products. Robotics and IoT devices play critical roles in enabling automation, data collection, and connectivity within Intelligent Manufacturing environments. Additionally, Digital Twin technology facilitates virtual simulation, modelling, and optimisation of production systems. While Intelligent Manufacturing offers significant benefits, it also presents challenges viz. high investments, integration complexity, and workforce reskilling requirements. Overcoming the challenges requires a holistic approach involving collaboration between industry stakeholders, government agencies, academia, and technology providers. Overall, Intelligent Manufacturing represents a promising future for the manufacturing industry, offering opportunities for innovation, competitiveness, and sustainable growth in a rapidly evolving global economy. 2025 selection and editorial matter, Alka Chaudhary, Vandana Sharma, and Ahmed Alkhayyat individual chapters, the contributors. -
Removal of Struvite in Wastewater Using Anammox Bacteria
Struvite precipitation in wastewater has proved to be an effective method in treating wastewater and has helped in the recovery of ammonia nitrogen and phosphate phosphorus. Nutrient recovery from wastewater has become a new trend attracting the interests of several researchers. Extraction of the nutrients based on struvite crystals as nutrition sources from wastewater has been acknowledged as a need of the hour solution to tackle the water pollution issue. This review focuses on the featured characteristics of struvite as a chemical fertilizer for plant and the struvite formation process related to physiochemical conditions in wastewaters. In the present work, struvite precipitation in the actual swine wastewater is studied by strategically controlling aeration, pH, and mixing of anammox bacteria. The effect of organic solids in the wastewater has also been studied. Laboratory experiments were conducted by optimizing pH value. pH was found to be an important parameter in the simultaneous removals of ammonium nitrogen and orthophosphate. This work reveals that the struvite removal from wastewater can be reduced to 80% using anammox bacteria. Springer Nature Singapore Pte Ltd. 2022. -
Analysis and Prediction of Suitable Model for Coconut Production Estimates in South Indian States
The study attempts to forecast coconut production in major coconut-producing states in India. The future projections on coconut production have been calculated based on yearly data for 73 years (194950 to 202122) accessed from the database of Indiastat (2022). We have used prominent forecasting techniques for the purpose and a suitable model has been chosen based on the lowest results of MAPE. The damped linear trend has been chosen for forecasting coconut production in Karnataka whereas Differenced first-order Auto Regressive model with drift has been adopted for Kerala and Karnataka. This study has considered a large dataset compared to other existing works and has chosen states that produce coconut on a large scale in India. Along with this, this study also attempts to find which state will produce more nuts for the Indian coconut industry, which can help the concerned stakeholders to take necessary decisions. Future projections depict that Kerala will continue to be the largest producer of coconut and Karnataka will show remarkable performance in coconut production during the upcoming four years post-study period. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Machine learning approaches towards medical images
Clinical imaging relies heavily on the current medical services' framework to perform painless demonstrative therapy. It entails creating usable and instructive models of the human body's internal organs and structural systems for use in clinical evaluation. Its various varieties include signal-based techniques such as conventional X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) imaging, and mammography. Despite these clinical imaging techniques, clinical images are increasingly employed to identify various problems, particularly those that are upsetting the skin. Imaging and processing are the two distinct patterns of clinical imaging. To diagnose diseases, automatic segmentation using deep learning techniques in the field of clinical imaging is becoming vital for identifying evidence and measuring examples in clinical images. The fundamentals of deep learning techniques are discussed in this chapter along with an overview of successful implementations. 2023, IGI Global. All rights reserved. -
Empowering Renewable Energy Using Internet of Things
The massive communication of information over network gadgets associated with the internet trades data starting from one to another with no sort of human cooperation. As innovation is advancing, interconnected organizations give data to each other to impart. The energy utilization is happening at an extremely quick rate, debilitating the assets in delivering it at a similar rate, and the entirety of this requires a transformation to save energy. Information is the focal point of the Internet of Things (IoT), and it has all the information to which there was no entrance before; this information can be utilized in the revolution of the energy management framework. By utilizing advanced IoT innovations, the embracement of renewable can be upgraded signifcantly further. The reconciliation of IoT in renewable energy is empowering its development by and large. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.