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Using Sentiment Analysis to Identify Consumers Emotions in the Hotel Industry
This research attempted to present a more comprehensive overview of online user-generated data by extending far beyond quantitative analysis. We gathered a distinctive and substantial database of online user ratings for the hotel industry from numerous websites over a significant amount of time. To gauge the quality of hotel service, we divided customer reviews into two categories using the sentiment analysis technique. The impact of those factors in influencing users overall evaluation and content creation behavior is then investigated. The findings imply that different aspects of user evaluations have considerably diverse effects on how users evaluate products and what motivates them to create content. 2025 by Apple Academic Press, Inc. -
Green Supply Chain Management: Attaining Sustainable Competitive Advantage
[No abstract available] -
Analytics Enabled Decision Making Tracing the Journey from Data to Decisions
In the current business environment, which is greatly dynamic and competitive, business organizations are continually striving for expanding their competence and financial performance through improving almost every facet of their business--product/service quality, customer satisfaction, customer retention, productivity, line filling strategies, and others. In this sense, success and failure of organizations depend on the extent of precision of their decisions. Organizations are engaged with data to extract insights, identify trends and make decisions at different levels; and also, many of them learn how to utilize the power of data. Analytics can enable them to derive conclusions, make predictions, and ascertain actionable insights in a contextual and time-bound manner. It helps to examine data from multiple perspectives and gives visualizations by using different frameworks and platforms such as IBM Watson, Tableau, and R. The chapter presents the role of analytics in decision-making processes and assess the effectiveness of decisions upon their implementation, so the corrective measures can also be inserted. As decision making is a continuous business process, analytics accelerates it and gives organizations a pace to keep updated with changing business scenarios. Thus, this chapter presented a decision-making framework exhibiting how decision-making functions as an ongoing process. Different contexts and cases have been used to establish the relevance of each step of the framework. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Detection of breast cancer in mammography images using intelligent models
Amongst the several cancer types, incidence of breast cancer is the highest in women. Breast cancer can be diagnosed and treated effectively through various screening methods and computer-aided detection systems (CADs). However, conventional computer-aided diagnosis (CAD) programs for detecting potential cancers on mammograms are lacking diagnostic accuracy and require upgradation. The advances in machine learning, particularly with the use of deep (multi-layered) convolutional neural networks, have allowed artificial intelligence to create a transformation in CAD that has improved models' prediction quality. The outline of this chapter includes a structured method for predicting presenting breast cancer stages, identification, segmentation and classification of lesions, and breast density assessment using the current technological models which includes artificial intelligence, deep learning, and machine learning. 2024, IGI Global. All rights reserved. -
A Systematic Literature Review on Image Preprocessing and Feature Extraction Techniques in Precision Agriculture
Revolutions in information technology have been helping agriculturists to increase the productivity of the cultivation. Many techniques exist for farming, but precision agriculture (PAg) is one technique that has gained popularity and has become a valuable tool for agriculture. Nowadays, farmers find it difficult to get expert advice regarding crops on time. As a solution, image processing techniques (IPTs) embedded PAg applications are developed to support farmers for the benefit of agriculture. In recent years, IPT has contributed a lot to provide a significant solution in PAg. This systematic review provides an understanding on preprocessing and feature extraction in PAg applications along with limitations. Preprocessing and feature extraction are the major steps of any application using IPTs. This study gives an overall view of the different preprocessing, feature extraction, and classification methods proposed by the researchers for PAg. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Delving into the Bubble Detection of Specific NSE Sector Indices
This study meticulously examines market bubbles within specific sectors of the National Stock Exchange (NSE) over the period from January 2017 to December 2023, employing robust methodologies like RADF, SADF, and GSADF tests. The analysis, centered on 11 sectoral indices, integrates GSADF values with RADF and SADF, offering nuanced perspectives that underscore the sector-specific nature of bubbles. Notably, the study highlights bubble occurrences during the 2020 global crisis due to pandemic, emphasizing their dynamic and diverse manifestations amid the pandemic. Exclusive identification of bubbles in NSE IT, NSE Metal, and NSE Pharma enriches the strategic insights available to investors, facilitating informed decision-making and risk management. The sector-wise approach contributes to a holistic understanding of market dynamics, providing investors with valuable tools to navigate the intricacies of the financial landscape. Future research avenues may delve into regulatory impacts on sector-specific bubbles and explore the interplay between macroeconomic indicators and sectoral bubbles, offering deeper insights into market dynamics. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Analyzing Risk-Return Trade-Offs Using ARCH and GARCH Models of the BRICS Countries
This study investigates financial markets in BRICS nations (Brazil, Russia, India, China, and South Africa) from 2003 to 2023. It examines mean returns, volatility, skewness, and kurtosis, assessing normality and data stationarity. ARCH-GARCH models uncover conditional heteroskedasticity and volatility clustering. It also explores mean reversion and momentum effects in the Nifty and MOEX indices. Findings show negative, near-zero mean returns, except for SSEC, which is modestly positive. Serial correlation suggests past values impact current returns. Volatility varies, with MOEX and SSEC having higher levels. ARCH-GARCH models indicate volatility clustering and non-normal return distributions. Mean reversion and momentum effects are identified in Nifty and MOEX, benefiting investors, financial institutions, and policymakers. This research informs investment strategies, risk management, and financial forecasts in BRICS economies, contributing to the understanding of the global financial landscape and potential contagion effects. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Interconnected Dynamics of Gold, Nifty, Crude Oil, and USD/INR: Insights from a Panel Data VAR Analysis
This study utilizes a panel data vector autoregression (PVAR) model to examine the relationships between Gold, Nifty, Crude Oil, and USD/INR, drawing from 3105 observations sourced from Yahoo Finance. Descriptive statistics reveal notable volatility, particularly in Gold and Crude Oil. Unit root tests confirm stationarity, crucial for time series analysis. Optimal lag selection recommends a lag order of 2, balancing model accuracy and complexity. Granger causality tests indicate limited predictive power, with gold influencing USD/INR unidirectionally. Impulse response function analysis and variance decomposition underscore Golds relative independence. Robustness tests affirm stability, highlighting USD/INRs endogeneity. This study enhances understanding of financial dynamics, offering insights for risk management, portfolio diversification, and monetary policy. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Security Threats and Privacy Issues in Cloud Data
The quick advancement of Web-based applications has led to a huge amount of information being scanned and gathered for business examination or scholarly research purposes, which may disregard individual protection. Organizations, industries and individuals data are at stake. In this paper, utilizing on the Web Personal Health Record (PHR) as contextual analysis, first demonstrate the need of inquiry ability approval that lessens the security introduction coming about because of the list items, and build up a versatile structure for authorized private keyword Search (APKS) over encoded cloud information. This particular model proposes two novel answers for APKS given on-going cryptographic crude, hierarchical predicate encryption (HPE). Our answers empower efficient multi-dimensional watchword looks with a run question, permit assignment and renouncement of hunt abilities. Additionally, the proposed system improves the question protection which conceals clients inquiry watchwords against the server. Actualize our plan on an advanced workstation, and exploratory outcomes exhibit its appropriateness for reasonable use. Privacy has seen advancement lately as information mining of the datasets in a dispersed huge information condition has turned into a successful worldwide business which is none other than data management or data analytics which ensures the security of data. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
AI applications at the scheduling and resource allocation schemes in web medium
Resources including business, informational, personal, and financial resources are required, with support from users, to maintain and implement the resource representations. Resource provisioning seeks to meet user needs by supplying the appropriate resources at the appropriate time at a lower cost. A service provider oversees supplying resources to all applications, and among the methods of resource management that they can employ are time-based, cost-based, on-demand, and bargain-based. These general approaches to resource provisioning and scheduling are based on recent developments in heterogeneity in 6G networks, including cloud computing, fog computing, and autonomic computing, to allocate and schedule resources while keeping an eye on service performance and adjusting as needed to meet the needs of cloud users. The proposed work increases resource allocation through cost reduction and, as a result, increases the availability of the services at the device levels without compromising performance parameters such as availability, efficiency, authentication, and authorization. The wide metropolitan area network (6G Networks) wireless heterogeneity is presented in this chapter's technological problems. Memory, network performance, and other factors were heterogeneous in fog nodes. Here, the Load balancing algorithm's Priority ordering is applied to make use of wireless model properties. This chapter focuses on various load balancing and scheduling strategies along with a few machine learning techniques applied to fog nodes and clustering techniques. 2024 selection and editorial matter, Dr. Abraham George and G. Ramana Murthy; individual chapters, the contributors. -
Empirical Assessment of Artificial Intelligence Enablers Strengthening Business Intelligence in the Indian Banking Industry: ISM and MICMAC Modelling Approach
Considering the context of the issue based on literature survey and expert opinion, this study investigates the drivers of Artificial Intelligence (AI) implementation, which further strengthens the Business Intelligence (BI) in taking better decision-making industries in India. For the purpose of serving the objective of examining the enablers towards having a smarter AI ecosystem in banking, the relevance of identified enablers from exhaustive literature survey were discussed with the experts from banking sector and AI professionals. Based on their opinion, 15 final enablers were defined based on the data collected have been put through Interpretive Structural Modelling (ISM) that reveals the binary relationship between the enablers to draw a hierarchical conclusion, and then assess the enablers about their independence, linkage, autonomous character, and dependence based on their calculated driving and dependence power through MICMAC analysis. The ISM and MICMAC integrated approaches have been used to establish interdependence among the enablers of AI in banking in India context. The study reveals that strong algorithms result in building quality AI information, and also the efforts from management related to commitment, financial readiness towards technological advancement, training, and skill development are quite essential in making the baking system smarter and would enable the industry to take better management decision. 2023 selection and editorial matter, Deepmala Singh, Anurag Singh, Amizan Omar & S.B Goyal. -
Modified Non-local Means Model for Speckle Noise Reduction in Ultrasound Images
In the modern health care field, various medical imaging modalities play a vital role in diagnosis. Among the modalities, Medical Ultrasound Imaging is the most popular and economic modality. But its vulnerability to multiplicative speckle noise is challenging, which obscure accurate diagnosis. To reduce the influence of the speckle noise, various noise filtering models have been proposed. But while filtering the noise, these filters exhibit limitations like high computational complexity and loss of detailed structures and edges of organs. In this article, a novel Non-local means (NLM)-based model is proposed for the speckle reduction of Ultrasound images. The design parameters of the NLM filter are obtained by applying the Grey Wolf Optimization (GWO) to the input image. The optimized parameters and the noisy image are passed to the NLM filter to get the denoised image. The efficiency of this proposed method is evaluated with standard performance metrics. A comparative analysis with existing methods highlights the merit of the proposal. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Quality Efficacy Issues in Mangoes: Decoding Retailers Supply Chain
This research article tries to uncover the elements and compelling reasons causing supply chain inefficacy concerning low quality at the retailer level of the mangoes supply chain in Karnataka. The descriptive research approach was used in work. The research was conducted in the biggest mango-producing areas of Karnataka. Factors were discovered by factor analysis. A systematic questionnaire was used to determine how much the mango sector may improve supply chain efficacy. Contingent on the factor analysis, four variables for low quality were identified: functional difficulties, knowledge, Manpower, and resources. It was also discovered that the functional component is the compelling factor causing supply chain inefficacy. The study is confined to the retailer level of the Mango supply chain, focusing on four Mango-producing districts in Karnataka. Furthermore, the measures for the key causes under each aspect causing hindrances in supply chain efficiency in terms of quality have been discovered. There is a scarcity of materials to enhance the supply chain efficiency of merchants in Indias mango business. This research attempted to address a literature gap and help practitioners improve the mango supply chain in underdeveloped nations. This paper also serves the 2nd goal, Zero Hunger, End starvation, improve food security and nutrition, and promote sustainable agriculture of sustainable development. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
Higher education institutions as a catalyst for sustainability development
Growing concerns about the planet and society have led to the evolution of the concept of sustainable development. This concept gained popularity when the World Commission on Environment and Development released its report Our Common Future in 1987. In 1975, United Nations Educational, Scientific and Cultural Organization (UNESCO) brought sustainability as the International Environmental Education Program focusing on environmental education. This gave birth to the idea that Higher Educational Institutions (HEIs) can play a significant role in promoting the sustainability agenda. Over the years, this was done by implementing sustainability initiatives on the campus. These initiatives mostly focused on the environment and ignored the social and economic dimensions of sustainability. Given the paucity of adequate knowledge in this field, the chapter aims to explore the challenges in implementing sustainable initiatives and suggest a framework that will guide HEIs to act as a catalyst for sustainability development. 2024, IGI Global. All rights reserved. -
Bioremediation of Heavy Metal Contaminated Sites Using Phytogenic Nanoparticles
Heavy metals (HMs) accumulate in milieu due to various human activities that persist leading to biomagnification in food chains and cause unpleasant effects on human health and environment. Pollutants such as organic matter and HMs are reme-diated traditionally by chemical precipitation, electrochemical treatment, adsorption, reverse osmosis, ion exchange, coagulation, and photo-catalyzation, remained inef-fective. Use of nanomaterials conjugated with various compounds showed significant reduction in several contaminated sites. However, existing implication of nanotech-nology works with nanoparticles (NPs) synthesis majorly involved the use of chem-ical raw materials and physical methods which are relatively toxic and unstable. Aforesaid difficulties made researchers and entrepreneurs to reconnoitre effective, newer, and novel synthesis approaches for the replacement over older version. During the past decade, to overcome these issues plant-derived NPs are extensively used because of its less cost, efficiency, and eco-friendly in nature. Hence, advanced alternative technology like phytoremediation using nanomaterials with innovative techniques has been a boon for HM remediation. Efficiency of green synthesized NPs is based on redox reactions which makes metals stable facilitated by flavonoids and polyphenols responding to HM-stress. Several metal complexation processes are known to produce phytochelatins or other metal-chelating peptides helping the biore-mediation of HMs. Current chapter throws light on adaptive mechanism employed by NPs coupled with plant or microbial extracts in overcoming the HM stress. Further-more, here we also focus on the possible mechanism and interaction between NPs and HM in minimizing severity of polluted sites with many examples. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
From Beans to Business: A Rise of Coffee Preneurs in Kodagu, Karnataka
Coffee is the world's third most consumed beverage after water and tea. India stands at the 7th position as the largest coffee exporter globally, with a significant contribution of 72.5% from Karnataka and 33% from Kodagu alone. This region plays a crucial role in the country's coffee industry, making it a vital component of India's economy, and 80% of the residents of Kodagu rely on coffee cultivation for their livelihood. Coffee farming is considered an annual crop that requires the generated income to be cycled to the subsequent year's coffee cultivation. Planters face numerous challenges during their production, which forces them to sell or convert their agricultural lands into concrete lands (buildings) or convert them into resorts, thereby changing their occupation, which makes coffee sustainability questionable. Therefore, coffee farmers have recently adopted an entrepreneurial approach to augment their income sources and support their livelihoods and occupations. This study aims to assess the key drivers of coffee farmers opting for entrepreneurial activities to assist coffee farming in Kodagu, Karnataka. This study has revealed that additional income, passion for farming, business skills, available resources, opportunity, satisfaction, innovation, creativity, unfair market prices, education, and socialising platforms are the key determining factors for coffee farmers to choose entrepreneurship. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Forest Fire Prediction Using Machine Learning and Deep Learning Techniques
Forests are considered synonyms for abundance on our planet. They uphold the lifecycle of a diversity of creatures, including mankind. Destruction of such forests due to environmental hazards like forest fires is disastrous and leads to loss of economy, wildlife, property, and people. It endangers everything in its vicinity. Sadly, the presence of flora and fauna only increase the fire spread capability and speed. Early detection of these forest fires can help control the spread and protect the nearby areas from the damage caused. This research paper aims at predicting the occurrence of forest fires using machine learning and deep learning techniques. The idea is to apply multiple algorithms to the data and perform comparative analysis to find the best-performing model. The best performance is obtained by the decision tree model for this work. It gave an accuracy of 79.6% and a recall score of 0.90. This model was then implemented on front-end WebUI using the flask and pickle modules in Python. The front-end Website returns the probability that a forest fire occurs for a set of inputs given by the user. This implementation is done using the PyCharm IDE. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Data Security
Corporates, industries, and governments have completely digitized their infrastructure, processes, and data or running towards completed digitalization. This data could be text files, different types of databases, accounts, and networks. The data living in the digital format needs to be preserved and also protected from unauthorized access. If this data remains open for access, any unauthorized user can destroy, encrypt, or corrupt the data, making the data unusable. There are implications of data security threats such as data breaches and data spills, beyond cost and can spell doom for the business. Hence the data needs to be protected from such threats. Data security is a mechanism through which data is protected and prevented from loss due to unauthorized access. It is a mix of practices and processes to ensure data remains protected from unauthorized use and readily accessible for authorized use. Data Security is essential for achieving data privacy in general. To define appropriate security measures, we must define the difference between a data breach and a data leak. Data security mechanisms could be data-centric such as identity and access management, encryption and tokenization, and backup and recovery. A defined data governance and compliance can also ensure data security. This chapter will explain why there is a need for data security, methods and processes to achieve data security, and touch upon some of the data security laws and regulations. We will also see a case study on how hackers exploited a vulnerability to mount a data security attack worldwide and how data security mechanisms could have prevented it. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Intellectual Property Right - Copyright
The power of cognition of human beings is beyond the imagination of any cognitive person. As gifted and nurtured property, the intellect of human beings has the potential to be original, creative, and innovative. Has the human being got absolute control over her/his intellect? Can human beings possess absolute rights over any product of her/his intellect? How far is a human being indebted to society? If human beings are not given due credit to the product of her/his intellect, the enthusiasm to be more creative and productive may take a coarser path. Human beings have the fundamental right to use her/his intellect to live a life of their choice enjoying economic and non-economic benefits. The right to intellectual property is fundamental to human beings. Hence, any infringement of intellectual property has to be dealt with appropriately. At the same time, human beings should be indebted to society for nurturing their intellect. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Data Ethics
Ethics is all about living an ethical life. As rational beings, humans have always been in the pursuit of ethical life in spite of the contrary temptations. Society and engagement in society are helpful for a person to be ethical. However, it is the choice one makes in critical situations that define the ethical nature of a person. Swarmed by a vast pool of data, the complex nature of ethical decision-making is getting far more complex for human beings with autonomous cognitive faculty. One needs to be conscious and focused to face any dilemma in ones life. Dealing prudently with private and public data and understanding the science of data would help the homo sapiens to prove her/his relevance in this data-driven world. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.