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A Machine Learning- Based Driving Assistance System for Lane and Drowsiness Monitoring
Lane line detection is a vital component when driving heavy vehicles; this concept follows the path for driving a vehicle to prevent the risk of accidentally entering another lane without the drivers knowledge, which could result in an accident. To detect the lane, use frame masking and Hough line transformation with efficient machine learning algorithms, pre-processed and trained adequately for optimum accuracy as per the provided dataset to spot the white markings on both sides of the lane. Long-distance truck drivers suffer from sleep deprivation, making driving extremely dangerous while tired and they ignore the line markings and wander into the wrong lane. This chapter proposes a portable system that does not require any sensors or interference with the vehicles wiring system; instead, a system that fits on a windshield or any surface to monitor the actions of the driver, using computer vision and feature-extracted datasets within a trained neural network model using cameras. This driver-assisted system can detect drowsiness and give an alarm to wake up the driver by identifying the Region of Interest. These predictions are made based on eye movements, and the algorithm generates a score. The higher the score, the longer the time between alarms. 2024 Taylor & Francis Group, LLC. -
Biomass Derived Fluorescent Nanocarbon Sensor for Effective Sensing of Toxic Cadmium Metal Ions
Cadmium ion (Cd2+) is common in our surroundings and may readily bioaccumulate into the organism following passage through the respiratory and digestive systems. Chronic exposure to Cd2+ can lead to considerable bioaccumulation in an organism because of its longer biological high life (1030 years), which permanently harms the health of humans and animals. Considering this hazardous effect of toxic Cd2+ metal ions, there is a need to develop a toxic-free and simple sensor synthesized from easily available and biocompatible biomass or natural precursor. Herein we report the effective synthesis and development of a fluorescence sensor from Indigofera tinctoria (L.), a well-known medicinal plant via one step green, hydrothermal synthesis method. The remarkable fluorescence and larger stokes shift make it ideal for fluorescence sensing strategy. This sensor detects potentially toxic Cd2+ assisting fluorescence sensing strategy in the metal ion concentration range from 1 nM to 1 M. The SternVolmer plot exhibits a remarkable linear detection range exhibiting limit of detection (LOD) as 14.74 nM. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Rational Designing of Ni-Ag/C Bimetallic Nanoparticles
Bimetallic nanoparticles have been found to show improved properties due to the synergistic effect between the incorporated metals as a result of electronic charge transfer between them. The importance of using bimetallic particles lies in the high selectivity that they offer. Ni being a reactive metal, was doped with Ag, a highly selective host. In this study, Ni-Ag bimetallic nanoparticles supported on carbon have been synthesized by co-impregnation by using nickel (II) nitrate and silver nitrate as precursors. The catalyst is characterized using XRD, FTIR, DLS, Zeta potential, EDX, SEM, and TEM. The scope of this synthesized catalyst can be extended to several reactions like CO2 reduction reaction, hydrogenation, and industrially important organic reactions. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Comparative Analysis of Various Ensemble Approaches for Web Page Classification
The amount of data available on web pages is enormous, and extracting the relevant information and classifying them is an important task. Web page classification finds applications in web content filtering, maintaining and expanding web directories, building efficient crawlers, etc. Machine Learning methods known for their well-established classification approaches have proved to be effective in web page classification. The present work uses ensemble methods like Bagging Meta Estimator, Random Forest, Adaptive boosting, Gradient Tree boosting, Extreme Gradient boosting and stacking to improve single classifiers results. One dataset is manually created to classify web pages into IoT projects and non-IoT projects. Another publicly available dataset is used to classify publications- and conference-related web pages. The advantage of the Ensemble methods over single classifiers has been validated, and various parameters to tune the Ensemble classifiers have been presented and analysed, with accuracy being the metric for performance. Features like learning rate, number of estimators, and maximum number of features have been tuned besides other parameters, and a comparison has been presented. 2023 Scrivener Publishing LLC. -
Conversational Agents and Chatbots: Current Trends
Languages facilitate the communication and interaction process among people. Computers learn to communicate with humans intelligently with the help of conversational agents and chatbots based on Natural Language Processing (NLP). Conversational agents and chatbots are gaining popularity in various applications. The development of chatbots or conversational agents is tightly coupled with an organizations customer service requirement. However, the background procedures that power the bots brain are more or less dependent on Artificial Intelligence-based processes. NLP mechanisms powered by various Deep Learning techniques are often used in the training and development of such intelligent agents. These bots inevitably become more competent as they interact with more people. The interactions between a customer and the bot are usually used as data in further training iterations. Chatbots are likely to respond with faster and more precise suggestions leading to solutions for frequently asked questions. Therefore, the current trends indicate the need for a supplementary system rather than substituting human agents existing customer service. The customer experience and intelligence of the chatbots are improved with the help of data analysis and training with the use of Deep Learning techniques. The chapter covers the current trends of conversational agents and chatbots, how the various Artificial Intelligence techniques have transformed the development of multiple architectures of these intelligent systems, and it compares the different state-of-the-art NLP-based chatbot architectures. 2024 selection and editorial matter, Anitha S. Pillai and Roberto Tedesco. -
ML Algorithms and Their Approach on COVID-19 Data Analysis
This chapter begins with characterizing Supervised Learning and Unsupervised learning and investigates Machine Learning algorithms in every one of the sub domains of Regression, Classification, Clustering, and so forth. It also talks about the engineering of calculations like Linear Regression, Logistic Regression, K-Means, K Nearest Neighbors, Hierarchical, DB Scan, Decision Tree, Random Forest Regression, and Random Forest classifier. Utilization of every algorithm to investigate the dataset will be displayed by carrying out it on renowned dataset model, and output of each piece of code is displayed with their preview. This section likewise takes care of the issue of predicting the future number of COVID-19 cases and the precision behind each model or algorithm is shown and investigated utilizing different measurements dependent on situation or issue articulation, for example, either issue is on forecast or order. This chapter does not focus on the solution of COVID-19 data analysis or expectation, rather it will be followed and will task different models dependent on need with conclusive target being clear comprehension of the Machine Learning algorithms and its execution in Python. 2023 Scrivener Publishing LLC. -
IDS for Internet of things (IoT) and Industrial IoT Network
The Internet of Things (IoT) is a swiftly increasing domain of interconnected gadgets, technologies, and structures that may be achieved in a small, tightly associated environment or can travel across big geographic areas, including Smart Cities. IoT devices are increasingly deployed for numerous goals inclusive of records sensing, accumulating, and controlling. The IoT enhances user affairs by permitting a huge variety of smart gadgets to link and possible information. IoT gadgets are hastily evolving universally while IoT offerings have become pervasive. IoT devices include a big assortment of devices, along with small, embedded sensors, AI assistants, digital cameras, and so on, which can be found in various backgrounds, i.e., Smart Homes, Smart Communities, and Smart Cities. Smart Cities have developed into intriguing areas with technologies consisting of traffic-conscious streetlights which dynamically react to emergencies by editing site visitors styles. Moreover, with the adoption of 5G networks, technologies and techniques throughout towns have become blended. This persevered improvement of IoT advocated the expansion of sophisticated and complicated systems which appreciably adjust the community. However, these technologies have guided to a brand new threat to the security of grids. Many present-day malware assaults, targeted at classic computer systems linked to the Internet, will also be required for IoT gadgets. With those enhancements, malicious actors have found new methods to control their weaknesses. One of the biggest cyber-attacks in instances of terabits in step with 2d operated, infected IoT gadgets harmonized within a botnet provides a massive DDoS assault which disrupts the Internet range for large geographic regions. This attack underlines the increasing hazard posed via uncertain IoT devices. Moreover, attacks that include those are evolving as greater threats as a larger quantity of exposed gadgets is introduced to networks throughout the globe. Their actions are anomalous and higher are the numbers of hazards and assaults toward IoT devices. Cyber-attacks arent new to the IoT, however as the IoT may be deeply interwoven in our lives and societies, traditional protection resolutions are inadequate when managing these dangers. Oftentimes, safety answers are created to run locally on host appliances, i.e., antivirus software, or as standalone machines (i.e. community firewalls and intrusion detection structures (IDSs). However, the IoT has obtained a clean set of community protocols, together with Zigbee, Ant+, and 6LoWPAN, that traditional safety solutions, such as rule-primarily based firewalls and host-based total antivirus software programs, had been not equipped with or have no longer been revised to account for. Moreover, many IoT gadgets suffer from computational, storehouse, or network situations. Due to those constraints, IoT safety answers, especially an IoT IDS, must be lightweight enough, in phrases of the computational, garage, and networking resources, to be living on the devices but sturdy enough to accurately hit upon potential intrusions. Therefore, a holistic method needs to be regular while coming to IoT intrusion detection. IoT devices cant be considered in a vacuum as self-contained machines due to the fact a totally fledged, modern protection answer is just too aid-annoying for constructing on those gadgets. The normal safety of the network necessitates IoT gadgets to be included as associates within a security answer rather than as man or woman nodes. Therefore, green protection of IoT devices could keep millions of net customers away from malicious moves. However, present malware detection techniques are afflicted by excessive computational complexity. Hence, theres a real necessity to protect the IoT, which has therefore resulted in a requirement to completely recognize the threats and assaults in an IoT infrastructure. 2024 selection and editorial matter, Mayank Swarnkar and Shyam Singh Rajput; individual chapters, the contributors. -
Changing Structure of Consumer Buying Behaviour and Expectation in the Digital Era
The growing digital landscape has made a fundamental impact on consumer behaviour. The digital era has totally transformed the buyers and shifted them from the traditional approach to the digital technologies. Todays digitally literate consumers have grown out of the TV advertisement experience to a wide range of digital marketing communications on their smartphone, tabs and laptops and on various social media. Marketers are geared up to identify, reach and engage these latest species of consumers who are agile and active in this new digital ecosystem having multiple devices and multiple channels. This new digital savvy customers give the marketers biggest challenges and rewards over their traditional counterparts. Today customers have some indispensable hopes and demands while they are shopping. The customers expect their needs of products and services should be met at their own time and at their own place, and at reasonable price. Digital era has empowered todays customers by providing them with easy and quick access to voluminous information, compare and contrast between brands and their offerings, facility to purchase the brand offerings from diverse devices and gadgets and also giving them the opportunity to dispense their post-purchase knowledge and experiences. Customer shopping habits have evolved with technology, and companies continue to adapt to maintain relevance. This study examines the consumer behaviour during the digital era. This paper also attempts to understand consumer sentiments and new buying behaviours in this digital era. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Unobtrusive Engagement Detection through Semantic Pose Estimation and Lightweight ResNet for an Online Class Environment
Analysing student engagement in a class through unobtrusive methods enhances the learning and teaching experience. During these pandemic times, where the classes are conducted online, it is imperative to efficiently estimate the engagement levels of individual students. Helping teachers to annotate and understand the significant learning rate of the students is critical and vital. To facilitate the analysis of estimating the engagement levels among students, this paper proposes a dual channel model to precisely detect the attention level of individual students in a classroom. Considering the possible inaccuracy of emotion recognition, a dual channel is configured with a Lightweight ResNet model for macro-level attention estimation and a 3d pose estimation using Euler angles for Pitch, yaw and roll that is trained, validated and tested on the Daisee database. The Emotional detection extracts the context of Engaged, frustrated, confused and disgust as higher levels of classroom attention cognition while the facial pose coordinates provide the real-time movement of the faces in the video to provide a series of engaged and disengaged coordinates. The Lightweight ResNet Model achieves a 95.5% accuracy and the Pose estimation test is able to distinguish the test videos at 92% as Engaged and Bored on the Daisee Dataset. The Overall Accuracies using the Dual channel was curated to 87%. 2023 Scrivener Publishing LLC. -
Implementation Strategies for Green Computing
In this chapter, we look at how renewable energy sources can be integrated into the planning, design, and construction of long-term sustainability in green buildings. When it comes to establishing a framework for environmentally friendly building, there are two primary schools of thought. One is related to the use of conventional architecture and low-energy construction material. The fundamental focus of green building design is on using renewable energy solutions for the purpose of managing energy protection. When referring to a green building, either sustainable construction or green construction may be used instead. To guarantee a structure will last for its intended purpose and the environment will not be harmed in the process, sustainable construction practices should be included from the start. Additionally, the economics of renewable energy are presented in this chapter with eco-friendly construction practices that make use of renewable energy sources. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa. -
Digital Game Addiction and Children
Nowadays the usage of digital games has increased a lot. Console games, PC games, and online games are all examples of digital games. Aside from these, it has been observed that digital games are also played with portable technologies such as mobile phones and tablets. Childrens play equipment, play habits, and play perceptions have all changed as a result of these changes. As a result, digital games have a significant influence on children. This chapter focuses on the effects of digital games on children and how children became addicted to digital games. It also discusses how to avoid overusing digital games. It also explains the meaning of digital games and discusses their history and future. 2023, IGI Global. -
Antibacterial Effect of Phosphorous-Doped Carbon Nanomaterial Derived from Alstonia Venenata
Antibiotics have been widely used as fundamental medicine for several decades to treat various bacterial infections. However, bacteria develop different mechanisms to defeat the action of antibiotics, which has become a significant issue that endangers infectious therapy. To reduce the consumption of antibiotics and thus combat the increasing antibiotic resistance, it is necessary to implement safe and effective alternatives to conventional antibiotics. Though nanomaterials have become an emerging hope in infectious treatments, they have limited application due to aggregation, toxicity issues, and problems related to their dispersibility. However, carbon nanomaterials (CNMs) offer high solubility, biocompatibility, and minimum toxicity with their inherent antibacterial properties. The selection of natural precursors as the carbon source is an eco-friendly and economical route for synthesizing antibacterial carbon nanomaterials. In the present work, fluorescent CNMs have been synthesized by the hydrothermal treatment of Alstonia venenata leaf extract. The antibacterial capability of the bare extract (AVE), hydrothermally treated extract (AVH), AVH doped with nitrogen (N-AVH), and AVH doped with phosphorous (P-AVH) are tested against gram-positive Staphylococcus aureus (S. aureus) and gram-negative Escherichia coli (E. coli) bacteria. Except for P-AVH, all other samples showed nontoxicity towards the tested bacterial species. In contrast, P-AVH inhibited bacterial growth with minimum inhibitory concentration (MIC) values of 2.5 and 2mg/ml on S. aureus and E. coli, respectively. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Cybersecurity Disclosure and Corporate Reputation: Rising Popularity of Cybersecurity in the Business World
This chapter emphasizes the importance of cybersecurity for a corporation as todays organizations are more vulnerable than ever and their enemies are in the form of viruses and malware. The work provides evidence that cybersecurity can have an impact on brand value, market value, and overall corporate reputation. It focuses on depicting the global scenario with reference to cybersecurity disclosures by corporations and how it is important in todays digitized era where data is the most valuable and vulnerable asset. With rapid digitalization, cybersecurity has become a major concern for all businesses, especially when there is financial and reputational damage to cybersecurity breaches and incidents. Even in the absence of clear cybersecurity laws and regulations, corporations are opting for voluntary disclosure. Existing literature explains this as an attempt to mitigate any potential risk or occurred risk through increased transparency which will build the trust of all stakeholders. 2023 by IGI Global. All rights reserved. -
Importance of Sustainable Marketing Initiatives for Supporting the Sustainable Development Goals
Businesses that engage in sustainable marketing can benefit both the world and their bottom line. Earlier, companies could satisfy many customers by simply providing low pricing and high-quality goods. However, peoples concern for the environment and other social concerns have grown, and so has their desire to support groups that share their beliefs. Because they often generate strong market returns and demonstrate durability during economic downturns, many investors want to support businesses that use sustainable business methods. Also, these businesses are more likely to comply with social and environmental laws. Several companies use sustainable marketing to succeed in todays ethical and ecologically sensitive marketplace. Organizations must finance sustainability programs in order to practice sustainable marketing. But, it can also improve employee engagement, promote regulatory compliance, raise revenues, and build brand loyalty. 2023 by IGI Global. -
Efficacy of Artificial Neural Networks (ANN) as a Tool for Predictive Analytics
Predictive analytics could also be defined as the application of statistical techniques and mathematical modeling to anticipate the future performance and expected return on investments. Predictive analytics examines the most recent and the historical data to see if the same pattern is likely to reoccur or not. This gives an opportunity to businessmen and financial investors to make an appropriate decision about their investments and expected returns. Ever since the development of ANN technique, researchers have tried to create a number of predictive models using ANN. The chapter is focused on defining predictive analytics and the tools used in predictive analytics, with a special orientation on Artificial Neural Networks. The objective of the chapter is to establish ANN as an effective technique for making appropriate predictions and thereby contributing toward the decision-making in various spheres using the outcomes from various researches. The chapter also aims to explain the step-by-step process of ANN in outcome prediction with the help of example. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Decolonizing the Mind: Invoking the Vernacular Experience in a Postcolonial Language Classroom
This chapter attempts to understand the teaching-learning practices, programmes, courses, and pedagogies of an English department that recently co-opted cultural studies as a means of decolonisation in a private university in India to understand how cultural diversity, learner diversity, teacher experiences, and learner interests became considered factors in language learning pedagogies and selection of learning content. The research will employ mixed methods of qualitative and quantitative techniques of course content analysis, student interviews to gauge the impact of the learning on the decolonisation process, teacher interviews to understand approaches to task design, and the intended outcome and the strategies and perception changes in material production and task development when the learning shifted to the online mode as a result of the pandemic disruption. 2023 by IGI Global. All rights reserved. -
Platform Business Model for Intelligent Supply Chain Operations
Platform economy involves technology to connect the dispersed network of participants. The Platform Business Model denotes a triangular participation between; the platform itself, the supplier and the consumer. The global market is witnessing a rise of digital platforms with an increase in the power of algorithms and cloud-based computing, connecting millions of participants in the network. The technological advancement makes the digital platforms a formidable force that ushers in change and brings out economic revolution across the globe. Many entrepreneurs have been created by these platforms, the workforces have the freedom to choose their work time and job, leading to an economically vibrant society. Platform businesses exist across various verticals, even in manufacturing setup. A variety of goods can be produced in a flexible assembly line. Hence the concept of outsourcing may require new definition from low-cost labour-based countries to high technology low-cost countries. There may be a transformation of economies shifting towards service, as major manufacturers may reorient themselves into service operators. Overall, the platform business model would make the entire operation more transparent with real time data transfer between the participants, leading to efficiency across the entire chain of business activities. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Strategies for Sustainable Practices in a Post-Pandemic World
We know from experience that possessions dont better themselves with time. In order to generate income, we must work. So, what do sustainability experts in the global business-school community recommend companies do when calamity begins to subside and some kind of reality is restored? Companies worldwide have suffered greatly from the COVID-19 pandemic. As a result of the epidemic, businesses are being forced to develop long-term strategies that are both profitable and sustainable in terms of society, the economy, and the environment. There is little doubt that businesses contribute significantly to the overall gross domestic product (GDP) of any nation. Because of the pandemic, businesses had to work even harder to reduce waste, adapt to changing demands from customers in record speed, and achieve peak performance alone. This has further raised the status of sustainability to one of moderate significance. Businesses must develop novel and cutting-edge approaches to ensure economic, environmental, and social longevity. Scholars have yet to settle on a single definition due to the business model's complexity. A study found that COVID-19 had both positive and negative impacts on educational technology (edtech) companies. As a result of the pandemic, businesses in the edtech sector no longer needed to make the case for the importance of their products in classrooms. Second, there was a rise in the acceptance of online education among educators. Also, edtech companies grew rapidly and benefited greatly from user feedback, and investors showed a lot of interest in the sector. However, due to the obstacles, sales discussions were either put on hold or cancelled. Edtech companies were unable to expand into new areas as a result of travel limitations. The purpose of this research is to investigate the link between the elements of sustainable development that contribute to the occurrence of enterprises and edtech enterprise employment and interest. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa. -
The Role of Financial Analytics in Decision-Making for Better Firm Performance
The need to make informed decisions has become a matter of survival for every organisation in the current unprecedented and dynamic business environment. The exponential growth in technology along with the internet has brought in enormous volume and variety of data access to all organisations irrespective of their industry. Organisations should consider their resources and industry environment to build their analytics capabilities, as it involves a tremendous investment. In this context, it is essential to understand the role of financial analytics in decision-making for better firm performance. Hence, this chapter proposes to throw light on the evolution of big data analytics, theoretical linkages, dimensions and benefits of using financial analytics, technological support for financial analytics along with use cases, and Strengths, Weaknesses, Opportunities, and Challenges (SWOC) analysis. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
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.