Book Chapters
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Item 3D printing of fly ash-based syntactic foams(Elsevier, 2021) Doddamani, M.; Gupta, N.In addition to the ease of fabrication using a wide range of forming processes, thermoplastic polymers are recyclable, which is a strong driving force behind their industrial applications. This chapter deals with manufacturing thermoplastic matrix lightweight composites called syntactic foams (SFs) using in the fused filament fabrication 3D printing process. High-density polyethylene (HDPE) is used as the matrix material and fly ash cenospheres are used as the filler. The development of SFs with cenospheres serves a dual purpose of beneficial utilization of industrial waste fly ash and a reduction in the component cost. Hollow fly ash cenospheres are mixed with HDPE to form a cenosphere/HDPE blend, which is extruded in the form of filaments for commercial 3D printers. Single-screw extruder parameters are optimized to develop eco-friendly SF filaments with minimum cenosphere fracture and homogeneous mixing of constituents. Fly ash-based SFs are successfully 3D printed for mechanical characterization and their properties are observed to be comparable to injection molded specimens of the same compositions. 3D printing of industrial components is successfully demonstrated with potential weight saving capabilities of 8% in addition to reduced polymer consumption to the tune of 4.64 million tons globally per year. © 2022 Elsevier Inc. All rights reserved.Item 3D Printing of Syntactic Foams for Marine Applications(Springer International Publishing, 2020) Gupta, N.; Doddamani, M.Syntactic foams are hollow particle filled lightweight composite materials that are widely used in structural applications in underwater marine vessels. Additive manufacturing (AM), also called 3D printing, methods are now being developed for printing parts of syntactic foams. These methods provide advantage that the entire part can be printed without the requirement of machining or joining and eliminates stress concentration locations. The present work is focused on describing the method of creating a syntactic foam filament for fused filament fabrication type printers and then developing parameters for printing syntactic foams parts using commercial printers. High density polyethylene resin is used as the matrix material with fly ash cenospehres and hollow glass microballoons as the fillers for creating syntactic foams. One of the major challenges is to minimize the fracture of hollow particles during filament manufacturing and 3D printing, which is addressed by parameter optimization during processing. Results show that the syntactic foam specimens are successfully printed and their properties are comparable to the injection molded specimens of the same compositions. © Springer Nature Switzerland AG 2020.Item 5-(Halomethyl)furfurals(Elsevier, 2025) Dutta, S.5-(Halomethyl)furfurals, derived from biomass-derived carbohydrates, act as renewable platform chemicals for the sustainable synthesis of industrially important organic chemicals. The historical background, physicochemical properties, production routes, reactivity patterns, and derivative chemistry of 5-(halomethyl)furfurals developed over the past century can assist in better comprehending their pivotal roles in the carbohydrate-centric biorefinery for the sustainability of the chemical industry and circular carbon economy. © 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.Item 5G to 6G: Empowering the Workforce Skills for Next-Gen Connectivity(IGI Global, 2025) Anurag, A.S.; Swathi, A.; Ramesh, R.; Johnpaul, M.The global launch of 6G communication is anticipated to occur in the near future. This high- speed communication technology will propel the growth of disruptive technologies that are currently underperforming due to our limited communication capabilities. With the establishment of 6G, advancements in AI, the Internet of Things, Machine Learning, and Edge Computing will reach new heights. These changes in the technological landscape will redefine workforce skills requirements. This chapter aims to examine the technological transformations resulting from the shift from 5G to 6G, particularly in the context of empowering workforce skills. Utilizing existing literature, the authors identified several workforce changes and proposed strategies to adapt to this evolving landscape. As communication speeds and data transfer rates increase, society will transition completely towards a smart and digital era. This paper will assist researchers, policymakers, and management personnel in preparing for the changes that 6G technology will bring. © 2025 by IGI Global Scientific Publishing. All rights reserved.Item A brief review of titanium (Ti)-based bioimplants fabricated using various additive manufacturing methods(CRC Press, 2024) Praharaj, A.K.; Suvin, P.S.; Bontha, S.In recent years, a noticeable growth has been observed in the research and development of manufacturing methods for biomedical implants. Extensive research has been conducted for orthopedic and dental implants due to their huge market size worth 4.5 billion dollars. Titanium (Ti) and its alloys are the most widely acknowledged biomaterials used in the production of orthopedic and dental implants due to their intriguing physical and biological properties including higher mechanical strength, excellent corrosion resistance, and biocompatibility. Apart from pure titanium (CP-Ti) and Ti-6Al-4V alloy, β-titanium has recently emerged as one of the important biomaterials for specific orthopedic applications due to its harmless chemical composition and low modulus. Over the years, Ti-based bioimplants were manufactured by conventional machining techniques which were less economical. With the growing demand across the world for the fabrication of customized biomedical implants, researchers were focusing on the development of new approaches and techniques for these implants. Recently, additive manufacturing (AM) has emerged as a potential fabrication method for biomedical implants due to its ability to produce customized products in less time with higher precision and flexibility. In addition, AM-fabricated bioimplants have shown improved osseointegration when compared to conventionally processed implants. In this chapter, various AM methods used for the fabrication of Ti-based implants were summarized with a special focus on the process parameters, microstructure, and related mechanical properties of the end product. Further, the effect of porous structures on the performance of Ti-based bioimplants was highlighted. This study will be helpful in identifying the pros and cons of AM methods in the manufacturing of bioimplants and leads to the advancement of research direction in biomedical sectors. © 2025 selection and editorial matter, Abhilash P M, Kishor Kumar Gajrani and Xichun Luo.Item A Class of Frozen Regularized Gauss-Newton Methods Under Weak Conditions(Springer, 2025) George, S.; Jidesh, P.Qinian Jin (2010) studied Frozen Regularized Gauss Newton Method (FRGNM) for approximating a solution of nonlinear ill-posed equation. The assumptions used to prove results in Jin’s paper are too restrictive. In this study, we analyze the convergence of FRGNM under weaker assumptions. This way we extend the applicability of FRGNM to the problems which does not satisfy the assumptions in Qinian Jin (2010). We also provide numerical results obtained for five different parameter choice strategies for FRCNM. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.Item A comparative analysis of machine comprehension using deep learning models in code-mixed hindi language(Springer Verlag service@springer.de, 2019) Viswanathan, S.; Anand Kumar, M.; Padannayil, K.P.The domain of artificial intelligence revolutionizes the way in which humans interact with machines. Machine comprehension is one of the latest fields under natural language processing that holds the capability for huge improvement in artificial intelligence. Machine comprehension technique gives systems the ability to understand a passage given by user and answer questions asked from it, which is an evolved version of traditional question answering technique. Machine comprehension is a main technique that falls under the category of natural language understanding, which exposes the amount of understanding required for a model to find the area of interest from a passage. The scope for the implementation of this technique is very high in India due to the availability of different regional languages. This work focused on the incorporation of machine comprehension technique in code-mixed Hindi language. A detailed comparison study on the performance of dataset in several deep learning approaches including End to End Memory Network, Dynamic Memory Network, Recurrent Neural Network, Long Short-Term Memory Network and Gated Recurrent Unit are evaluated. The best suited model for the dataset used is identified from the comparison study. A new architecture is proposed in this work by combining two of the best performing networks. To improve the model with respect to various ways of answering questions from a passage the natural language processing technique of distributed word representation was performed on the best model identified. The model was improved by applying pre-trained fastText embeddings for word representations. This is the first implementation of machine comprehension models in code-mixed Hindi language using deep neural networks. The work analyses the performance of all five models implemented, which will be helpful for future researches on Machine Comprehension technique in code-mixed Indian languages. © Springer Nature Switzerland AG 2019.Item A comprehensive security framework for WBANs in the healthcare environment(CRC Press, 2024) Pabitha, B.; Sanshi, S.; Karthik, N.The emergence of technology is constantly required by human society's healthcare system, where a patient is added to the environment of sickness every day. By providing real-time monitoring of patient vital signs, enabling remote patient care, and enhancing general medical diagnostics, Wireless Body Area Networks (WBANs) in e-healthcare have revolutionized the healthcare business. In our fast-paced environment, it is impossible to monitor every patient individually. Instead, WBAN can be used to treat patients in life-threatening situations. A new wireless network called WBAN was created using many tiny, short-power sensor nodes, communication links between nearby nodes, and a central base station to store and analyze the data. WBAN uses low-power, low-cost hardware with a 10 Kbps to 10 Mbps data rate. Many industries, including healthcare, senior care, sports and fitness, chronic illness management, military and emergency services, innovative apparel and fashion, precision agriculture, and farming, can successfully implement WBAN. These WBANs can be made using wearable digital apparel, accessories, and other items. In this chapter, WBAN is used in the healthcare system to monitor the fundamental values of temperature, pressure, blood sugar, and other parameters using a larger number of sensor nodes, transmit the monitored information promptly to a nearby base station (server), and then conduct data analysis to determine the patient's status accurately. As a result, tracking nodes and data transfer protocols must be highly secure to ensure data integrity. Here, strategies for potential node failures, improved technology for data connection faults, and corrective measures are provided to ensure confidentiality, integrity, and availability (CIA) for accurate analysis of patient data collection. However, there are significant privacy and data security issues that have been brought up by the use of WBANs in healthcare settings. This chapter offers a thorough security framework to handle the particular problems WBANs in e-healthcare provide. To guarantee the confidentiality, integrity, and accessibility of sensitive patient data, the framework includes encryption, authentication, access control, and intrusion detection technologies. Adopting contemporary security measures will lead to better patient outcomes and a more robust and secure healthcare ecosystem, promoting confidence between patients, healthcare providers, and technology. © 2025 selection and editorial matter, Anuj Kumar Singh and Sachin Kumar. All rights reserved.Item A comprehensive survey on federated cloud computing and its future research directions(Springer Science and Business Media Deutschland GmbH, 2021) Shishira, S.R.; Kandasamy, A.The cloud computing paradigm is popular due to its pay-as-you-go model. Due to its increasing demand for service, the user has a huge advantage in paying for the service currently needed. In a federated cloud environment, there is one or more number of cloud service providers who share their servers to service the user request. It improves minimizing cost, utilization of services and improves performance. Clients will get benefited as there is a Service Level Agreement between both. In the present paper, survey is provided on the benefits of the federated environment, its architecture, provision of resources and future research directions. Paper also gives the comparative study on the above aspects. © Springer Nature Singapore Pte Ltd 2021.Item A computational study on the stenosis circularity for a severe stenosed idealized artery(Pleiades journals, 2019) Prashantha, B.; Anish, S.Narrowing of blood vessels (stenosis) changes the nature of blood flow through the arteries. The altered flow structures at the downstream of stenosis may generate adverse effects on the arterial wall. Hence, an understanding of the effect of stenosis circularity on the flow behavior at the downstream of stenosis is clinically beneficial. The present study has been carried out on idealized stenosed artery model with severe case of stenosis (75% area reduction) but with the same cross-sectional area that has been selected for the study. The effect of different physiological states (pulse rates) study has been examined through using FLUENT Inc. solver by finite volume method, controlled through user-defined functions. The results indicate that the velocity profiles, oscillatory shear stress, and fluid residence time are significantly affected by the shape of the stenotic region. Fluid residence time in the downstream plays a significant role in understanding the hotspots for the secondary deposition/plaque. © Springer Nature Singapore Pte Ltd. 2019.Item A deep dive into Hyperledger(Institution of Engineering and Technology, 2021) Punathumkandi, S.; Sundaram, V.M.; Prabhavathy, P.Hyperledger is an open -source, network -oriented effort made to propel cross industry blockchain developments. It is a worldwide facilitated exertion remembering pioneers for banking, cash, Internet of Things, manufacturing, supply chains, and advancement. The Linux Foundation has Hyperledger under the establishment. This chapter gives an elevated level overview of Hyperledger: why it was made, how it is represented, and what it would like to accomplish. The core of this chapter presents five convincing uses for big business blockchain in various ventures. It depicts how the Hyperledger guarantees the secure, progressively solid, and increasingly streamlined communication. © The Institution of Engineering and Technology 2021.Item A Firefly Optimization Algorithm for Maximizing the Connectivity in Mobile Wireless Sensor Network(Springer, 2020) Mamatha, M.; Manjappa, K.For the effective functioning of a Mobile Wireless Sensor Networks (MWSN), the connectivity maintenance of the sensor nodes is of significant concern. Otherwise, it may result in an independent node or nodes wholly get detached from the network. Though such detached sensor nodes are functioning correctly and have good energy backup, its service cannot be utilized for the purpose it is intended for as it is isolated from the core network. These sensor nodes are sophisticated tiny devices and costlier depending on the application; therefore, proper care should be taken to keep them connected to the network. Hence, a firefly based algorithm, a Swarm Intelligence technique, referred to as Firefly Algorithm for Connectivity in Mobile WSN (FACM) has been proposed in this article in order to establish proper connectivity among the sensor nodes in MWSN. FACM is based on the insect fireflies, which have a unique feature of producing light, a result of chemical reaction, at different intervals to escape from the predators and most of the time to attract prey. The inevitable feature of insect firefly, attracting the prey, is exploited in the proposed FACM where a brighter sensor node (in terms of energy and distance) will attract the less bright neighboring sensor nodes. Thus, the less bright sensor node can depend on the brighter sensor node for the data transfer, thereby saving its energy. A fitness function has been designed based on the combination of two parameters energy and the distance, which decides the brightness of the sensor node. The effectiveness of the proposed FACM has been theoretically analyzed and verified by simulation through MATLAB. The results obtained are compared with classical FA and are found to be inspiring. © 2020, Springer Nature Switzerland AG.Item A holistic approach to influence maximization(Springer International Publishing, 2017) Sumith, N.; Annappa, B.; Bhattacharya, S.A social network is an Internet-based collaboration platform that plays a vital role in information spread, opinion-forming, trend-setting, and keeps everyone connected. Moreover, the popularity of web and social networks has interesting applications including viral marketing, recommendation systems, poll analysis, etc. In these applications, user influence plays an important role. This chapter discusses how effectively social networks can be used for information propagation in the context of viral marketing. Picking the right group of users, hoping they will cause a chain effect of marketing, is the core of viral marketing applications. The strategy used to select the correct group of users is the influence maximization problem. This chapter proposes one of the viable solutions to influence maximization. The focus is to find those users in the social networks who would adopt and propagate information, thus resulting in an effective marketing strategy. The three main components that would help in the effective spread of information in the social networks are: the network structure, the user's influence on others, and the seeding algorithm. Amalgamation of these three aspects provides a holistic solution to influence maximization. © Springer International Publishing AG 2017. All rights reserved.Item A Lightweight Convolutional Neural Network Model for Tuberculosis Bacilli Detection From Microscopic Sputum Smear Images(wiley, 2021) Panicker, R.O.; Pawan, S.J.; Rajan, J.; Sabu, M.K.This chapter describes a lightweight convolutional neural network model that automatically detects Tuberculosis (TB) bacilli from sputum smear microscopic images. According to WHO, about onefourth of the population in the universe is infected with TB, and every day five thousand people are killed due to TB disease. There are well-known recommended diagnostics are available for TB detection, among them sputum smear microscopic examination is a primary and most efficient recommended method for most of the developing and moderately developed countries. However, this manual detection method is highly error-prone and time-consuming. In this chapter, we proposed a lightweight CNN model for classifying Tuberculosis bacilli from non-bacilli objects. We adopted a Convolutional Neural Network (CNN) architecture with a skip connection of variable lengths that can identify TB bacilli from sputum smear microscopic images. The performance of the proposed model in terms of accuracy is close to the state-of-the-art. However, the number of parameters in the proposed model is significantly less than other recently proposed models. © 2021 Scrivener Publishing LLC.Item A novel hybrid algorithm for overlapping community detection in social network using community forest model and nash equilibrium(Springer Verlag service@springer.de, 2019) Sarswat, A.; Guddeti, R.M.R.Overlapping community detection in social networks is known to be a challenging and complex NP-hard problem. A large number of heuristic approaches based on optimization functions like modularity and modularity density are available for community detection. However, these approaches do not always give an optimum solution, and none of these approaches are able to clearly provide a stable overlapping community structure. Hence, in this paper, we propose a novel hybrid algorithm to detect the overlapping communities based on the community forest model and Nash equilibrium. In this work, overlapping community has been detected using backbone degree and expansion of the community forest model, and then a Nash equilibrium is found to get a stable state of overlapping community arrangement. We tested the proposed hybrid algorithm on standard datasets like Zachary’s karate club, football, etc. Our experimental results demonstrate that the proposed approach outperforms the current state-of-the-art methods in terms of quality, stability, and less computation time. © Springer Nature Singapore Pte Ltd. 2019Item A novel real-time face detection system using modified affine transformation and Haar cascades(Springer Verlag service@springer.de, 2019) Sharma, R.; Ashwin, T.S.; Guddeti, R.M.R.Human Face Detection is an important problem in the area of Computer Vision. Several approaches are used to detect the face for a given frame of an image but most of them fail to detect the faces which are tilted, occluded, or with different illuminations. In this paper, we propose a novel real-time face detection system which detects the faces that are tilted, occluded, or with different illuminations, any difficult pose. The proposed system is a desktop application with a user interface that not only collects the images from web camera but also detects the faces in the image using a Haar-cascaded classifier consisting of Modified Census Transform features. The problem with cascaded classifier is that it does not detect the tilted or occluded faces with different illuminations. Hence to overcome this problem, we proposed a system using Modified Affine Transformation with Viola Jones. Experimental results demonstrate that proposed face detection system outperforms Viola–Jones method by 6% (99.7% accuracy for the proposed system when compare to 93.5% for Voila Jones) with respect to three different datasets namely FDDB, YALE and “Google top 25 ‘tilted face’” image datasets. © Springer Nature Singapore Pte Ltd. 2019Item A novel technique of feature selection with relieff and CFS for protein sequence classification(Springer Verlag service@springer.de, 2019) Kaur, K.; Patil, N.Bioinformatics has gained wide importance in research area for the last few decades. The main aim is to store the biological data and analyze it for better understanding. To predict the functions of newly added protein sequences, the classification of existing protein sequence is of great use. The rate at which protein sequence data is getting accumulated is increasing exponentially. So, it emerges as a very challenging task for the researcher, to deal with large number of features obtained by the use of various encoding techniques. Here, a two-stage algorithm is proposed for feature selection that combines ReliefF and CFS technique that takes extracted features as input and provides us with the discriminative set of features. The n-gram sequence encoding technique has been used to extract the feature vector from the protein sequences. In the first stage, ReliefF approach is used to rank the features and obtain candidate feature set. In the second stage, CFS is applied on this candidate feature set to obtain features that have high correlation with the class but less correlation with other features. The classification methods like Naive-Bayes, decision tree, and k-nearest neighbor can be used to analyze the performance of proposed approach. It is observed that this approach has increased accuracy of classification methods in comparison to existing methods. © Springer Nature Singapore Pte Ltd. 2019Item A numerical study on heat transfer characteristics of two-dimensional film cooling(Pleiades journals, 2019) Ademane, V.G.; Hindasageri, V.; Kadoli, R.Determination of reference temperature and heat transfer coefficient in case of three temperature problems such as film cooling is one of the fundamental tasks in the design of gas turbines. In the present work, a two-dimensional numerical simulation is carried out for flat surface with 35° angle of injection from slot in case of film cooling problem. The reference temperature, which is represented as film cooling effectiveness, and heat transfer coefficient on the flat surface for different blowing ratio are studied. Heat transfer coefficient obtained from the present simulation is compared with the experimental results from the literature and found to be matching at lower blowing ratios. Turbulence intensity is found to a major contributor in enhancing the heat transfer coefficient. There is an increase in heat transfer with the blowing ratio due to increased turbulence intensity is observed. © Springer Nature Singapore Pte Ltd. 2019.Item A perspective of advanced biosensors for environmental monitoring(Elsevier, 2019) Mohan Balakrishnan, R.M.; Uddandarao, U.; Raval, K.; Raval, R.Biosensor technology has developed in leaps and bounds due to multidisciplinary approach between biotechnology and nanotechnology. This synergy provided much needed characteristic features, such as sensitivity and selectivity to the biosensor technology. Biosensors are venerated as superior entities for electrochemical, optical, and calorimetric-based sensing because of their exceptional size properties. They are the potential tools, which exhibited the feasibility and potential in detecting various biological, physical, chemical, radiological contaminants in water. This book chapter outlines the overview of various types of sensors, especially on chalcogen-based semiconductor nanoparticles. In this scenario, green route nanoparticles which employ PbSe quantum dots synthesis via marine Aspergillus terreus and ZnS/PbS nanoparticles via an endophytic fungus Aspergillus flavus are focused in this chapter. The book chapter also discusses about highly selective biogenic nanosensors which play a significant role in improving the capacity of biosensors due to their size tuneable quantum confinement effects. Potential applications of these biosensors for environmental monitoring are discussed. © 2019 Elsevier Inc. All rights reserved.Item A probe into the technological enablers of microservice architectures(Springer Verlag service@springer.de, 2019) Joseph, C.T.; Chandrasekaran, K.Microservice architectures (MSA), composed of loosely coupled and autonomous units called microservices, are gaining wide adoption in the software field. With characteristics that are loyal to the requirements of the Cloud environment, such as inherent support for continuous integration/continuous deployment (CI/CD), MSA are actively embraced by the Cloud computing community. Containers employing lightweight virtualization have also been increasingly adopted in the Cloud environment. The containers wrap applications along with their dependencies into self-contained units, which can be deployed independently. These features make it the unanimously accepted technology to enable seamless execution of microservices in the Cloud. With this outlook, this chapter undertakes a study on how containers may be used to support the execution of microservices. The study also includes other technologies that, in collaboration with container technologies, provide the support required for running microservices in the Cloud. An interesting concern for applications running on containers is resource management. Nevertheless, this is a significant aspect for supporting microservices as well. Such issues have been identified and research works addressing all or some of these issues, have been considered. The various relevant studies have been classified into different categories and the future directions have been identified, which can be used by researchers aiming to enhance the technological support for microservices in Cloud. © Springer Nature Singapore Pte Ltd. 2019.