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                <text>A Machine Learning- Based Driving Assistance System for Lane and Drowsiness Monitoring</text>
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                <text>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 &amp;amp; Francis Group, LLC.</text>
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                <text>Ramasamy S.A.G.</text>
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                <text>Machine Intelligence: Computer Vision and Natural Language Processing, pp. 193-208.</text>
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                <text>ISBN: 978-100096031-0; 978-103220199-3</text>
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                <text>Ramasamy S.A.G., Christ University, Bangalore, India</text>
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                <text>Biomass Derived Fluorescent Nanocarbon Sensor for Effective Sensing of Toxic Cadmium Metal Ions</text>
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                <text>Fluorescence sensing; Green synthesis; Nanocarbon sensor</text>
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                <text>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.</text>
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                <text>Neethu J.; Ann M.A.; Manoj B.</text>
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                <text>Springer Proceedings in Materials, Vol-28, pp. 265-269.</text>
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                <text>ISSN: 26623161</text>
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                <text>Neethu J., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bengaluru, India; Ann M.A., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bengaluru, India; Manoj B., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bengaluru, India</text>
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                <text>Rational Designing of Ni-Ag/C Bimetallic Nanoparticles</text>
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                <text>Bimetallic; Ni-Ag nanoparticles; Organic synthesis</text>
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                <text>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.</text>
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                <text>Anand S.; Sunaja Devi K.R.</text>
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                <text>Springer Proceedings in Materials, Vol-28, pp. 395-401.</text>
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                <text>ISSN: 26623161</text>
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                <text>Anand S., Department of Chemistry, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Sunaja Devi K.R., Department of Chemistry, CHRIST (Deemed to Be University), Bengaluru, 560029, India</text>
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                <text>Comparative Analysis of Various Ensemble Approaches for Web Page Classification</text>
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                <text>ensemble learning models; Machine learning; web page classification; web scraping</text>
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                <text>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.</text>
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                <text>Dutta J.; Kim Y.W.; Dominic D.</text>
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                <text>Data Engineering and Data Science: Concepts and Applications, pp. 137-172.</text>
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                <text>Joseph A., Department of Data Science, CHRIST Deemed to be University, Pune Lavasa Campus, India; Eapen N.G., Department of Data Science, CHRIST Deemed to be University, Pune Lavasa Campus, India</text>
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                <text>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.</text>
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                <text>Data Engineering and Data Science: Concepts and Applications, pp. 335-349.</text>
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                <text>Ashok K., Department of CS, Kyungpook National University, Daegu, South Korea; Reddy P.A., Department of CSE, Christ University, Karnataka, Bangalore, India; Kumar K.P., Department of CSE, Christ University, Karnataka, Bangalore, India</text>
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                <text>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.</text>
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                <text>Artificial Intelligence for Intrusion Detection Systems, pp. 117-132.</text>
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                <text>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.</text>
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                <text>Thiruthuvanathan M.M., Department of CSE, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Krishnan B., Department of Psychology, School of Social Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Rangaswamy M., Department of Psychology, School of Social Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India</text>
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                <text>Kaswan K.S., ITM Business School, India; Dhatterwal J.S., Koneru Lakshmaiah Education Foundation, India; Singh S.P., Rashtrakavi Ramdhari Singh Dinkar College of Engineering, India; Sharma V., Computer Science Department CHRIST (Deemed to be University), Delhi-NCR, India; Balusamy B., Shiv Nadar Institute of Eminence, Shiv Nadar University, Delhi NCR Campus, India</text>
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                <text>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.</text>
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                <text>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.</text>
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                <text>Varghese M.; Kootery K.P.; Sarojini S.; Balachandran M.</text>
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                <text>Varghese M., Department of Physics and Electronics, Christ University, Bengaluru, India; Kootery K.P., Department of Life Sciences, Christ University, Bengaluru, India; Sarojini S., Department of Life Sciences, Christ University, Bengaluru, India; Balachandran M., Department of Physics and Electronics, Christ University, Bengaluru, India</text>
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                <text>Cybersecurity Disclosure and Corporate Reputation: Rising Popularity of Cybersecurity in the Business World</text>
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                <text>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.</text>
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                <text>Lenka A.; Goswami M.; Singh H.; Baskaran H.</text>
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                <text>Effective Cybersecurity Operations for Enterprise-Wide Systems, pp. 169-183.</text>
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                <text>ISBN: 978-166849020-4; 978-166849018-1</text>
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                <text>Lenka A., CHRIST University (Deemed), India; Goswami M., CHRIST University (Deemed), India; Singh H., CHRIST University (Deemed), India; Baskaran H., Compose Corner, India</text>
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                <text>Importance of Sustainable Marketing Initiatives for Supporting the Sustainable Development Goals</text>
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              <elementText elementTextId="153829">
                <text>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.</text>
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              <elementText elementTextId="153830">
                <text>Anuradha A.; Shilpa R.; Thirupathi M.; Padmapriya S.; Supramaniam G.; Booshan B.; Booshan S.; Pol N.; Chavadi C.A.; Thangam D.</text>
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                <text>Handbook of Research on Achieving Sustainable Development Goals With Sustainable Marketing, pp. 149-169.</text>
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              <elementText elementTextId="153835">
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                <text>ISBN: 978-166848683-2; 978-166848681-8</text>
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                <text>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.</text>
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