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A Study on Emotion Identification from Music Lyrics
The widespread availability of digital music on the internet has led to the development of intelligent tools for browsing and searching for music databases. Music emotion recognition (MER) is gaining significant attention nowadays in the scientific community. Emotion Analysis in music lyrics is analyzing a piece of text and determining the meaning or thought behind the songs. The focus of the paper is on Emotion Recognition from music lyrics through text processing. The fundamental concepts in emotion analysis from music lyrics (text) are described. An overview of emotion models, music features, and data sets used in different studies is given. The features of ANEW, a widely used corpus in emotion analysis, are highlighted and related to the music emotion analysis. A comprehensive review of some of the prominent work in emotion analysis from music lyrics is also included. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
A study on smart device application platform
Cloud Computing is considered to be one of the hottest research areas as it provides an approach through which the data is stored and accessed over the Internet in a virtual environment. The main idea to adapt this technology is that it shares the available resources rather than having separate local servers. This technology plays a crucial role in the healthcare sector as the healthcare industries believe that by incorporating cloud services within the healthcare sector it could provide quality services to the patients. Many industrial specialists suggest ways of converting the huge amount of data collected from the healthcare into meaning information and later sharing this valuable information to the user at the right time. The smart device is an electronic rig that is efficient to answer, sympathize and interact mutually with its users and other smart devices, one of the upcoming smart devices are smart shirts. Smart shirts allow the user to share information like Facebook or LinkedIn profile details. This paper focuses on providing wearable devices to the user in order to have monitored over his/her health. Springer Nature Singapore Pte Ltd. 2019 -
A survey on various applications of internet of things on blockchain platform
[No abstract available] -
A Sustainability Approach to Geopolymer Brick Manufacture Using Mine Wastes
India has tons of by-products of industries like fly ash, ground granulated blast furnace slag (GGBS), and mine tailings from different ores. By incorporating these wastes in bricks, the carbon footprint can be minimized. This research pivots around the use of iron ore tailings (IOT) and slag sand as a substitute for clay or shale in the manufacture of stabilized geopolymer blocks. Iron ore tailings and slag sand were used for substitution in the range of 20-40% and 15-40% with increments of 5%. Fly ash, ground granulated blast furnace slag, and sodium silicates (Na2SiO3) were used with a constant value of 15%. The bricks were cast and cured at ambient temperature. The study includes testing of mechanical properties of geopolymer bricks as per IS recommendations. To study the macroanalysis, SEM and XRD analyses were also carried out on raw materials and developed composites. The outcomes of this investigation show that the inclusion of 25% of IOT and 30% of slag sand is acceptable as brick material. Springer Nature Singapore Pte Ltd. 2022. -
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. -
A thorough investigation of various goals and responses for mobile software-defined networks
Cloud computing has caused some companies to modify their IT infrastructure and maintenance procedures and may eliminate their current hardware altogether. Conventional methods of setting up a switch or router may be error-prone and unable to make full use of the capabilities of current network architectures. As many intelligent networking designs as possible must be developed for intellectualization, activation, and customization in future networks. Due to software-defined networking (SDN) technology, it's possible to control, secure, and optimize network resources, eliminating the rigid coupling between the control plane and the data plane in traditional network architectures. Here, the chapter explores the problems, difficulties, and potential solutions associated with software-defined networks (SDN), a novel concept in computer networking. Through SDN, the network gains the ability to be programmable, quick, and adaptable thanks to its separation of data and its ability to control traffic. 2023, IGI Global. All rights reserved. -
Accounting fraud and bankruptcy: The case of wirecard AG
This chapter examines the scandal at Wirecard AG, a German payment processing and financial services company, that became one of the most valuable companies on the German stock exchange in the 2010s. From 2010 to 2018, Wirecard reported consistent revenue growth and profitability. In 2019, the company reported revenues of 2.8 billion ($3.2 billion). As of September 2018, its market capitalization was over 24 billion ($27 billion). In late 2019, the Wirecard scandal was discovered through investigative reports by the Financial Times, which raised questions about Wirecard's accounting practices. The company faced a major scandal in 2020 when it was revealed that 1.9 billion ($2.1 billion) was missing from its balance sheet. Subsequent investigations revealed a massive accounting fraud that had been going on for years. Subsequently, the company filed for bankruptcy. Multiple Wirecard executives, including its CEO, were charged with fraud and market manipulation. German regulators and auditors were criticized for failing to detect and prevent the fraud. 2023, IGI Global. -
Acculturative stress: Psychological health and coping strategies
There is an increasing shift in focus from the causes of immigration to the consequences of immigration, a major aspect being the stress triggered by the myriad changes and challenges experienced during the process of moving into a different culture and settling in. The main aim of this chapter is to introduce the reader to the concept of acculturative stress in detail. The author has gathered the content by doing a keyword search of relevant terms on Google Scholar and choosing articles that provide insight into acculturation, acculturative stress, and psychological health. The chapter will delve into how the different strategies of acculturation are associated with the level of acculturative stress experienced and consequent mental health problems as well as strategies to manage or reduce acculturative stress. 2023, IGI Global. All rights reserved. -
Achieving SDGs through MSMEs: An empirical assessment of environmental consideration initiatives in India
Today, addressing environmental concerns and reducing carbon emissions has become imperative for every organization. Hence, eliminating the adverse impacts of business operations is no longer limited to large organizations, even small business organizations are taking a proactive approach in this direction. The present study aims to investigate pertinent issues related to the adoption of environmental practices faced by MSMEs in India and how these practices can fulfill the aim of achieving sustainable development goals (SDGs 2030). However, in this chapter, the authors are only going to emphasize the environmental aspect of the sustainability dimensions. Further, this study also identifies the factors that impact the adoption of environmental consideration initiatives among MSMEs in India. The findings of the study offer significant contributions to the research related to environmental consideration initiatives of the Indian MSMEs sector. Further, it also highlights the need for mandatory frameworks and guidelines to facilitate the adoption of sustainability practices among MSMEs in India. 2024, IGI Global. All rights reserved. -
Active Learning from an Imbalanced Dataset: A Study Conducted on the Depression, Anxiety, and Stress Dataset
The proposed chapter deals with psychological data related to depression, anxiety, and stress to study how the classification and analysis is carried out on imbalanced data. The proposed study not only contributes on providing practical information about the balancing techniques such as synthetic minority oversampling technique but also reveals the strategy for dealing with the working of many existing classification algorithms such as the support vector machine, random forest, XGBoost, etc. on the imbalanced dataset. The present use of evaluation metrics that are solely implied for the imbalanced data classification is also illustrated. It was observed that the ordinary model assessment techniques do not precisely quantify model execution when gone up against imbalanced datasets and that the common techniques such as the logistic regression and decision tree have a predisposition toward classes that have many observations. The attributes of the minority class are treated low and are routinely overlooked. Henceforth, there is a high likelihood of misclassification of the minority class when compared to the majority class. A confusion matrix which contains data about the real and predicted class is used as an assessment standard to check the exhibition of grouping calculation. Rather than going for accuracy, F-score and the area under the curve are considered as the measures to evaluate the classification model. 2022 selection and editorial matter, Vishal Jain, Sapna Juneja, Abhinav Juneja, and Ramani Kannan. -
Activity Classifier: A Novel Approach Using Naive Bayes Classification
Activity movements have been recognized in various applications for elderly needs, athletes activities measurements and various fields of real time environments. In this paper, a novel idea has been proposed for the classification of some of the day to day activities like walking, running, fall forward, fall backward etc. All the movements are captured using a Light Blue Bean device incorporated with a Bluetooth module and a tri-axial acceleration sensor. The acceleration sensor continuously reads the activities of a person and the Arduino is designed to continuously read the values of the sensor that works in collaboration with a mobile phone or computer. For the effective classification of a persons activity correctly, Nae Bayes Classifier is used. The entire Arduino along with acceleration sensor can be easily attached to the foot of a person right at the beginning of the user starts performing any activity. For the evaluation purpose, mainly four protocols are considered like walking, running, falling in the forward direction and falling in the backward direction. Initially five healthy adults were taken for the sample test. The results obtained are consistent in the various test cases and the device showed an overall accuracy of 90.67%. Springer Nature Switzerland AG 2020. -
Adapting Case Study Pedagogy for Non-Residential Business Schools: Strategies for Implementation
Case study pedagogy is widely recognized as a powerful teaching approach in business education programs. However, its implementation in non-residential business schools poses distinct challenges. Optimizing case study pedagogy to the unique needs and circumstances of non-residential students necessitates a specific strategy. This chapter delves into various strategies essential for the effective implementation of case study pedagogy in non-residential business schools. First, an overview of 2024 by IGI Global. All rights reserved. -
Adapting palates: A mapping of food neophobia and neophilia in the shift towards sustainable food consumption
This research explores how two different personality traits-neophilia and neophobia-affect people's eating habits and preferences in the context of sustainable gastronomy tourism. Neophilia, which indicates an openness to trying new culinary experiences, contrasts with neophobia, which is defined as a fear of new foods. Data was collected from 234 gastronomy tourists in Bangalore to examine these dynamics. Smart PLS-SEM 4 was utilized for data analysis. The survey investigated the attitudes and behaviours of participants regarding sustainable food practices that they encountered while engaging in gastronomy tourism. The results show that food neophobia significantly improves people's perceptions of food quality, which further had a statistically significant favourable influence on sustainable consumption; it had no significant effect on post-consumption behaviour. The study highlights how vital gastronomy is to improving experiences, preserving local identity, and drawing tourists-particularly in the rapidly growing category of culinary tourism. 2024, IGI Global. All rights reserved. -
Adaptive artificial bee colony (aabc)-based malignancy pre-diagnosis
Lung cancer is one of the leading causes of death. The survival rate of the patients diagnosed with lung cancer depends on the stage of the detection and the timely prognosis. Hence, early detection of anomalous malignant cells is needed for pre-diagnosis of lung cancer as it plays a major role in the prognosis and treatment. In this work, an innovative pre-diagnosis approach is suggested, wherein the size of the dataset comprising risk factors and symptoms is considerably decreased and optimized by means of an Adaptive Artificial Bee Colony (AABC) algorithm. Subsequently, the optimized dataset is fed to the Feed-Forward Back-Propagation Neural Network (FFBNN) to perform the training task. For the testing, supplementary data is furnished to well-guided FFBNN-AABC to authenticate whether the supplied investigational data is competent to effectively forecast the lung disorder or not. The results obtained show a considerable improvement in the classification performance compared to other approaches like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Adoption of blockchain technology in the real estate sector toward the improvement of smart cities
The rapid urbanization of global population causes many social, economic, and environmental issues, which does significantly influence the quality of life and living conditions of the people over the past years. The idea of smart city has grown popular, and it brings the opportunity to solve these urban issues. The motives of smart cities are to create the best use of public resources, enhance the quality life of people, and provide high quality services. Also, smart cities benefit from innovative applications of new kinds of information and communication technology to support communal sharing. Blockchain technology (BT) is more helpful to promote the development of smart cities through the implementation of BT in all the sectors. Blockchain-based smart contracts are disrupting the smart real estate sector of the smart cities. With this background, the study aims to explore the adoption of green BT in real estate sector toward the implementation of smart cities. 2023 Elsevier Inc. All rights reserved. -
Adoption of digital technologies in the procurement process to improve supplier lead time
Supply chain is a complicated process involving a number of stakeholders. A proper integration of all the stakeholders helps to improve the efficiency of the system in terms of time, money and effort. Adoption of digital technology has been a hindrance in many industries, thereby affecting their business processes. The study aims to throw light on the adoption of digital technologies in procurement process to improve supplier lead time in the automotive industry. An observational study was conducted in a major automotive supply chain company in South India. Researchers tried to identify the possible contributing factors to improve supplier lead time and derive the root cause of the issue. A framework for an advanced shipping notice portal was created which can help both the supplier and recipient. Digital technology adoption can increase supply chain efficiency, decrease manual error rates, and streamline communication. Additionally, the portal can serve as a centralized hub for data sharing, promoting improved teamwork and real-time information sharing. 2024 by IGI Global. -
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. -
Advanced Load Balancing Min-Min Algorithm in Grid Computing
Framework figuring has turned into genuine distinctive to old supercomputing situations for creating parallel applications that bridle huge process assets. In any case, the quality acquired in building such parallel Framework mindful applications is over the ordinary parallel registering conditions. It tends to issues like asset disclosure, heterogeneous, adaptation to non-critical failure and assignment programming. Load balancing errand programming inconceivably indispensable downside in cutting edge lattice environment. Load balancing ways is normally utilized for the development of appropriated frameworks. Normally there is a three kind of stages related with Load compromise that is information arrangement, higher psychological process, learning Relocation. Take a gander at the impact of surveying on load assignment by contemplating a fundamental expense in limit. There are three completely hovered tallies to lift which put away the stack ought to be doled out to, pondering the framework action cost among get-togethers. These tallies utilize grouped data trade frameworks and an asset estimation framework to redesign the constrained air framework exactness of load adjusting. Springer Nature Switzerland AG 2020. -
Advanced Materials from Biomass and Its Role in Carbon-Di-Oxide Capture
This chapter explores utilizing agricultural waste for developing advanced materials for CO2 capture, overcoming drawbacks of conventional adsorbents. It compares biomass-based activated carbons CO2 adsorption capabilities to commercial adsorbents, highlighting promising performance. Strategies for enhancing selectivity and efficiency through functional group hybridization are discussed, alongside investigations into operational parameters effects on material properties and CO2 uptake. Additionally, the chapter reviews biomass-derived carbon materials role in CO2 capture, detailing conversion techniques like pyrolysis and hydrothermal carbonization. Various modification methods, including activation and N-doping, are examined for enhancing CO2 capture. Discussion extends to diverse advanced materials derived from biomass, including biochar and activated carbon. The chapter underscores the circular-economy impact of utilizing biomass-derived porous carbons in CO2 capture processes, particularly in biogas upgrading to biomethane. Overall, it offers insights into addressing CO2 capture challenges, proposing future research directions in this field. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Advances in sensor technologies for detecting soil pollution
The present chapter elucidates progressions in the surveillance of soil pollution, with a specific emphasis on integrated systems and sensor technologies. Future trends (e.g., enhanced selectivity, regulatory adoption), deployment platforms (field-deployable, wireless networks), and sensor types (electrochemical, optical, and biosensors) are discussed. Increasing sensitivity and specificity, facilitating on-site, real-time analysis, and integrating sensing with remediation strategies are priorities. The discourse highlights the revolutionary capacity that soil pollution sensors possess to propel environmental monitoring and management forward. Collaboration among stakeholders is critical for successfully implementing sensorbased approaches and driving innovation. 2024, IGI Global. All rights reserved.