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Nanomaterials for A431 Epidermoid Carcinoma Treatment
Malignancy is the ancient sickness that causes an increased rate of mortality worldwide. Traditional malignant growth treatments that are clinically utilized comprise chemotherapy, radiotherapy, and medical procedure. Despite the fact that there have been motivating enhancements in the nanotechnology and biomedical field, malignant growth remains the most urgent condition to treat, as the central reason for mortality. Nanotechnology has the possibility to improve medication transport and delivery by modifying pharmacokinetics and conveyance, resulting in reduced negative reactions and in this manner improving precision. Some issues exist regarding destinations and the difficulties that occur, and the potential for success becomes closer with every discovery. Nanomaterials are smaller in size than organic macromolecules. More correctly, they as a rule have a width of many nanometers (nm), which makes them from 100 up to multiple times smaller than even one malignancy cell. Nanoparticles can occur in sizes running from 10 up to 400nm, and can likewise be used with a simple set up or a blend of pharmacologically dynamic medications, depending on a superficial level of properties. The various aspect of nanotechnology for malignant growth treatment include exact targeting of the lively segments in cell/tissues, producing upgrades responsive medication discharge, defeating natural obstructions, interfacing against disease dynamic system with imaging atoms, improving disease examination, and imaging. For the most part, nanoparticles burdened with mending operators are conveyed experimentally for firm malignancy treatment. Todays nanotechnology is a magnificent platform for the treatment of differing malignant growths. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Smartphone Usage, Social Media Engagement, and Academic Performance: Mediating Effect of Digital Learning
Smartphone has penetrated across all regions of India and all sections of the society, especially among the higher education student community. Smartphones with the internet, in turn, provide access to social media platforms. Smartphones and social media (SM) together provide several benefits to the users, and they also cause unwanted repercussions on the users such as adverse mental health, addiction, and laziness. But one of the important gains of smartphone and social media usage (SMU) is digital learning through them. Smartphones and SM are inevitable in the academic process of higher education students. The students use extensively the smartphone and SM for sharing information and content, for having peer discussion, for managing assignments, and for communicating with the instructors. So, this study tries to study the mediating effect of digital learning through smartphones and SM on the educational accomplishment of private university students in Bangalore, India. This study adopted the survey method of research which collected primary data through structured questionnaires from the private university students. The collected data were analyzed using students t test, One-way ANOVA, Chi-Square, and Structural Equation Modeling. The study results found that smartphones and SM affect the academic performance (AP) of the sample students significantly through digital learning. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Data Privacy
Data privacy is a private and public phenomenon and its operations have implications for the individual and the society. This understanding of privacy ceases it from being viewed as a simple technological process and highlights different factors that are associated with it. While on one hand, the right to privacy is seen as integral to the freedom of the individual, on the other hand, it is also seen as the ability to hide certain information for malpractice. This chapter delves into this existing dichotomy of data privacy and simplifies various terms and operations that have emerged in the field of study. A discussion is facilitated on the concept and its associated areas. The chapter looks at privacy regimes in different countries to note emerging developments and also presents a critique of the practice to bring forth shortcomings and enable change. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Leveraging Blockchain Technology forInternet ofThings Powered Banking Sector
Banking sector contributes to 70% of Indian Gross Domestic Product (GDP) and for India to meet its economic aspirations, it should enable this vivacious sector to grow at 810 times of its current pace, in the next ten years. This pace of active growth requires a double engine of sophisticated technology and a tech enabled, scalable, and a secured banking system. Implementing BlockchainTechnology (BCT) in the banking sector, provides a realistic solution which when coupled with devices connected by the Internet of Things(IoT), will result in secured, fast-paced, cost effective, and transparent growth of the sector. The prevalence of personalized banking, secured banking, connected banking, and digital banking are use cases, made possible through interface with IoT. This chapter delves into the opportunities in the banking sector to be explored and challenges to be met in the BCT-IoT implementation process. BCT- and IoT-based opportunities such as peer-to-peer lending, Know Your Customer (KYC) updation, Cross-border transfer payments, syndicate lending, fraud reduction are some of the banking operations that are elaborated. To strengthen the banking network, the consensus algorithm of Blockchainnetwork is much required and the use of IoT devices to act as nodes is pertinent. The blend of both in the banking space has to be further reinforced. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Data and Its Dimensions
In current times Data is the biggest economic opportunity. As per the studies, it is observed that the world is becoming 2.5 quintillions data-rich every day, with an average of every human contributing 1.7MB of data per second. Every individual has a good appetite for data, as it gives immense insight to explore and expand the business. With the invention of smart devices and innovation in the field of connectivity such as 4G-5G Mobile Networks and Wi-Fi, the generation and consumption of the data are steadily increasing. These smart devices continuously generate data, leading to a bigger pool for better decision-making. This chapter presents data, the various forms and sources, and the concept of Data Science; it discusses how the ownership and value of data are decided; and also highlights the use, abuse, and overuse of the data along with data theft, and a case study to represent data breach. 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. -
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. -
Efficacy of Nanomaterials and Its Impact on Nosocomial Infections
Nanotechnology provides the ability to manipulate the properties of materials by using their size, and this has lead research towards a massive amount of plausible uses for nanomaterials. Irresistible maladies can occur, and they create an impressive burden on general wellbeing worldwide. The incident of these ailments is higher in developing nations. Irresistible maladies might be caused by microscopic organisms, infections, and protozoa, and the diseases they cause are often resistant to traditional treatment bringing about protracted contamination and higher mortality risk. In connection to that, the patients infected with these smaller scale creatures, that may prove resilient for an extended period of time, can be transmitters of these diseases to others. The recuperating of irresistible maladies is possible by metal-based nanoparticles that are plausible therapeutics for the treatment of irresistible ailments and their natural productivity. Metal-based nanoparticles that have been accounted for with antibacterial movement include silver, iron, iron oxide, copper oxide, zinc oxide, aluminum oxide, titanium dioxide, gold, and gallium nanoparticles. Present day improvements in nanotechnology enable us to handle this issue at two levels: diagnostics and treatment. Elimination of irresistible microorganisms requires effortless and exact recognition of the irresistible agents for suitable treatment. Various nanomaterials have been considered for the management of and cautious measures for irresistible ailments. Recently, nanomaterials have improved the treatment, diagnostics, and avoidance of irresistible illnesses. Built nanoparticles have been progressively utilized in irresistible infection management caused by microorganisms. Progress in nanoparticle-based frameworks involve a confident research region with basic ramifications for the recuperating of bacterial contaminations. Nanosystems have been shown to be beneficial, and different approaches dependent on nanoparticles have been expanded to see unambiguous agents. Various purpose-of-care (POC) tests have been anticipated that can propose results earlier, simpler, and at less expense than known strategies and can even be used in difficult to reach areas for viral determination. Quorum sensing is a boosts reaction substance formulation strategy interrelated with population density that microorganisms use to authorize biofilms development. Research is ongoing concerning the antimicrobial movement of nanoparticles, contrasting it by methods for and the motivation behind the natural extract of therapeutic plants, and concentrating on anti-toxin protections of pathogenic microscopic organisms. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
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. -
Group Key Management Techniques forSecure Load Balanced Routing Model
Remote sensor organizations (WSNs) assume a vital part in giving ongoing information admittance to IoT applications. Be that as it may, open organization, energy limitation, and absence of brought together organization make WSNs entirely defenseless against different sorts of pernicious assaults. In WSNs, recognizing vindictive sensor gadgets and dispensing with their detected data assume a vital part for strategic applications. Standard cryptography and confirmation plans cannot be straightforwardly utilized in WSNs on account of the asset imperative nature of sensor gadgets. In this manner, energy productive and low idleness procedure is needed for limiting the effect of malignant sensor gadgets. In this research work presents a secured and burden balanced controlling contrive for heterogeneous bunch-based WSNs. SLBR shows a predominant trust-based security metric that beats the issue when sensors proceed to influence from extraordinary to terrible state and the other way around; besides, SLBR alters stack among CH. In this way, underpins fulfilling superior security, allocate transmission, and vitality efficiency execution. Trials are driven to calculate this presentation of developed SLBR demonstrate over existing trust-based controlling show, particularly ECSO. The result accomplished appears SLBR demonstrate fulfills favored execution over ECSO as distant as vitality capability (i.e., arrange lifetime considering to begin with sensor contraption downfall and total sensor contraption passing), correspondence overhead, throughput, allocate planning idleness, and harmful sensor contraption mis-classification rate and recognizable verification. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Optimal Stacked Sparse Autoencoder Based Traffic Flow Prediction in Intelligent Transportation Systems
Recently, intelligent transportations system (ITS) has gained significant internet due to the higher needs for road safety and competence in interconnected road network. As a vital portion of the ITS, traffic flow prediction (TFP) is offer support in several dimensions like routing, traffic congestion, and so on. To accomplish effective TFP outcomes, several predictive approaches have been devised namely statistics, machine learning (ML), and deep learning (DL). This study designs an optimal stacked sparse autoencoder based traffic flow prediction (OSSAE-TFP) model for ITS. The goal of the OSSAE-TFP technique is to determine the level of traffic flow in ITS. In addition, the presented OSSAE-TFP technique involves the traffic and weather data for TFP. Moreover, the SSAE based prediction model is designed for forecasting the traffic flow and the optimal hyperparameters of the SSAE model can be adjusted by the use of water wave optimization (WWO) technique. To showcase the enhanced predictive outcome of the OSSAE-TFP technique, a wide range of simulations was carried out on benchmark datasets and the results portrayed the supremacy of the OSSAE-TFP technique over the recent state of art methods. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Impact of Blockchain Technology in the Healthcare Systems
The healthcare industry is one of the most important industries in the world which is in dire need of a restructuring process because of its poor and outdated techniques of data management. Healthcare system has adopted a centralized environment and deals with a lot of intermediaries which makes it prone to issues of single point of failure, lack of traceability of transactions, and privacy issues such as data leakage. Blockchain is a relatively new technology which is able to tackle the obsolete methods and practices existing in the healthcare industry. In this chapter, we analyzed the applications of blockchains in the healthcare industry which can solve the issues prevalent in the healthcare industry. The aim of this chapter is to reveal the potential benefits that comes from using blockchain technology in the healthcare industry and identify the various challenges that this technology has. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Supervised Learning-Based Data Classification and Incremental Clustering
Using supervised learning-based data classification and incremental clustering, an unknown example can be classified using the most common class among K-nearest examples. The KNN classifier claims, Tell me who your neighbors are, and it will tell you who you are. The supervised learning-based data classification and incremental clustering technique is a simple yet powerful approach with applications in computer vision, pattern recognition, optical character recognition, facial recognition, genetic pattern recognition, and other fields. Its also known as a slacker learner because it doesnt develop a model to classify a given test tuple until the very last minute. When we say yes or no, there may be an element of chance involved. However, the fact that a diner can recognise an invisible food using his senses of taste, flavour, and smell is highly fascinating. At first, there can be a brief data collection phase: what are the most noticeable spices, aromas, and textures? Is the flavour of the food savoury or sweet? This information can then be used by the diner to compare the bite to other items he or she has had in the past. Earthy flavours may conjure up images of mushroom-based dishes, while briny flavours may conjure up images of fish. We view the discovery process through the lens of a slightly modified adage: if it smells like a duck and tastes like a chicken, youre probably eating chicken. This is a case of supervised learning in action. Machine learning can benefit from supervised learning, which is a concept that can be applied to it (ML). 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Real-Time Application with Data Mining and Machine Learning
Data mining and machine learning are the most expressive research and application domain. All real-time application directly or indirectly depends on data mining and machine learning. There are manyrelevantfields, like data analysis in finance,retail, telecommunications sector, analyzing biological data, otherscientific uses, and intrusiondetection.The most expressive research and application domain is data mining and machine learning. Data mining and machine learning are used in all real-time applications, whether directly or indirectly. Data analysis in finance, retail, telecommunications, biological data analysis, extra scientific applications, and intrusion detection are just a few exampleswhere it can be used. Because it captures a lot of data from sales, client purchase histories, product transportation, consumption, and services, DM has a lot of applications in the retail industry. It's only logical that the amount of data collected will continue to climb as the Internet's accessibility, cost, and popularity increase. In the retail industry, DM assists in the detection of customer buying behaviors and trends, resulting in improved customer service and increased customer retention and satisfaction. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
A Brief Concept on Machine Learning
Machine learning is a subset of AI. Its a research project aimed at gathering computer programscapable of performing intelligent actions based on prior facts or experiences. Most of us utilize various machine learning techniques every day when we use Netflix, YouTube, Spotify recommendation algorithms, and Google and Yahoo search engines and voice assistants like Google Home and Amazon Alexa. All of the data is labeled, and algorithms learn to anticipate the output from the input. The algorithms learn from the datas underlying structure, which is unlabelled. Because some data is labeled, but not all are, a combination of supervised and unsupervised techniques can be used. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Play and Play Spaces for Global Health, Happiness, and Well-Being
Play has a significant role in an individuals learning and holistic development. Play and recreation are a need and right. Research on play indicates that the significance of play is neglected among the current generation. Play spaces are shrinking, and physical play is becoming extinct in most communities. This current scenario may or have led to poor physical and mental health outcomes. The proposed book chapter aims to present play and play spaces in physical and mental health. The literature of play theories in child development shows the role of play in socioemotional, physical, and cognitive development. The current paper brings together literature on play across the lifespan, highlighting how play and recreation impacts children, youth, adults, and older adults physical and mental health. The change in lifestyle patterns has contributed to the neglect of play and recreation. The paper throws light on the need for the attention of professionals and policymakers for interventions and advocacy at both local and global levels in promoting play and preserving natural play spaces. The Editor(s) (if applicable) and The Author(s), under exclusive license to Taylor and Francis Pte Ltd. 2022. -
Review on Segmentation of Facial Bone Surface from Craniofacial CT Images
Three-dimensional (3D) representation of facial bone surface is needed in the virtual surgical planning for orthognathic surgery. Segmentation of facial bone surface from computed tomography images is first step in developing the 3D model. With the advent in the computer vision techniques, various automatic and semi-segmentation algorithms were developed in the recent years for segmentation of facial bone surface from craniofacial computed tomography images. In the proposed paper, the various segmentation techniques for extracting bone surface from 3D CT images for corrective jaw surgery available in the literature have been discussed. By reviewing all the methods available in the literature, it is found that each method has its own merits and demerits. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Data Classification and Incremental Clustering Using Unsupervised Learning
Data modelling, which is based on mathematics, statistics, and numerical analysis, is used to look at clustering. Clusters in machine learning allude to hidden patterns; unsupervised learning is used to find clusters, and the resulting system is a data concept. As a result, clustering is the unsupervised discovery of a hidden data concept. The computing needs of clustering analysis are increased becausedata mining deals with massive databases. As a result of these challenges, data mining clustering algorithms that are both powerful and widely applicable have emerged. Clustering is also known as data segmentation in some applications because it splits large datasets into categories based on their similarities. Outliers (values that are far away from any cluster) can be more interesting than typical examples; hence outlier detection can be done using clustering. Outlier detection applications include the identification of credit card fraud and monitoring unlawful activities in Internet commerce.As a result, multiple runs with alternative initial cluster center placements must be scheduled to identify near-optimal solutions using the K-means method. A global K-means algorithm is used to solve this problem, which is a deterministic global optimization approach that uses the K-means algorithm as a local search strategy and does not require any initial parameter values. Insteadof selecting initial values for all cluster centers at random, as most global clustering algorithms do, the proposed technique operates in stages, preferably adding one new cluster center at a time. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Corporate Social Responsibility and Sustainability Development Mapping: Practical Application Beer and Nigel Roome Model
Toyota is one of the highly appreciated companies for CSR performance in India. The central theme of this research paper is to apply Beers and Nigel Roome model of sustainability to the Japanese automobile manufacturer operating in India. In the first part of analysis, we have discussed the relevance of Beers model to the Toyota CSR activity. In the second part of analysis, we make an effort to take forward the work of Basavaraj et al. (2018) who framed the questionnaire to map the Nigel Roome model to Toyota CSR case. The contribution of this case is to bring the new dimension in data presentation and analysis of Roome theoretical model on weak sustainability versus strong sustainability. The case analysis provides new insights for CSR managers to map their performance pictorially using Tableau software. Finally, we conclude, Toyota follows significant components of cybernetic model. Due to conscious effort of Toyota, India has positioned itself substantially well in the CSR ranking. 2022, Springer Nature Singapore Pte Ltd. -
Introduction to Data Mining and Knowledge Discovery
Data mining is a process of discovering some necessary hidden patterns from a large chunk of data that can be stored in multiple heterogeneous resources. It has an enormous use to make strategic decisions by business executives after analyzing the hidden truth of data. Data mining one of the steps in the knowledge-creation process. A data mining system consists of a data warehouse, a database server, a data mining engine, a pattern analysis module, and a graphical user interface. Data mining techniques include mining the frequent patterns and association learning rules with analysis, sequence analysis. Data mining technique is applicable on the top of various kinds of intelligent data storage systems such as data warehouses. It provides some analysis processes to make some useful strategic decisions. There are various issues and challenges faced by a data mining system in large databases. It provides a great place to work for data researchers and developers. Data mining is the process of classification, which can be executed based on the examination of training data (i.e., objects whose class label is predefined). With the help of an expert set of previous class objects with known class labels, it can find a model that can predict a class object with an unknown class label. These classification models can be classified into a variety of categories, including nearest neighbor, neural network, and others. Bayesian model, decision tree, neural network Random forest, decision trees Support vector machine, random forest SVM (support vector machine), for example. By analyzing the most common class among k closest samples, the K-Nearest Neighbor (KNN) technique aids in predicting of the class object with the unknown class label. Its an easy-to-use strategy that yields a solid classification result from any distribution. The Naive Bayes theory helps to perform the classification. It is one of the fastest classification algorithms, capable of efficiently handling real-world discrete data. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.