Book Chapters (June 2021)
KIIT School of Biotechnology
1. Mohanty, P., Singh, P. K., Chakraborty, D., Mishra, S., Pattnaik, R. (2021), Insight into the Role of PGPR in Sustainable Agriculture and Environment, Frontiers in Sustainable Food Systems, Vol. 5, No. 1, p. 183, DOI: 10.3389/fsufs.2021.667150.
Abstract: Plant growth promoting rhizobacteria (PGPR), representing microbial groups and with ability to colonise plant roots, influence plant growth through various indirect and direct modes and/or protect the plant from diseases or damages due to insect attack. PGPR produces indole acetic acid, ammonia, hydrogen cyanide, catalase, etc. It also improves nutrient uptake by altering the level of plant hormone that enhances root surface area by increasing its girth and shape, thereby helping in absorbing more nutrients. Hence, while developing a successful crop-specific PGPR formulation, the candidate rhizobacteria should possess characteristics like high rhizosphere competence, broad-spectrum action, safety towards the environment and compatibility with other partnering organisms.
2. Dey, G., Montet, D., Thonart, P. (2021), Probiotic Lactobacillus Strains for Enhanced Health Benefits (Genetic Engineering and Microencapsulation) in Probiotic Beverages, Panda, S.K., Kellershohn, J., and Russell, I. (Eds), Elsevier, Academic Press, USA, ISSBN: 978-0-12-818588-9, DOI; 10.1016/B978-0-12-818588-9.00015-2 , pp. 309–337.
Abstract: Genetically, engineered probiotic organisms are envisioned as the next new age functional products. The concerted ability of the engineered probiotic strains designed to recognize the target, synthesize, and deliver biomolecules at a specific site has made them popular biotherapeutics. Several evidences discussed in this chapter confirm the potential application of genetically modified probiotic strains in numerous conditions ranging from irritable bowel syndrome to hypertension and from phenylketonurea to tumor therapy and anti-infective. In the future, the tools of Clustered Regularly Interspaced Short Palindromic Repeats can be further modified to develop a diverse range of designer probiotic strains by swapping the promoter and therapeutics genes to target several other disease biomarkers and treatments, respectively. Considering the growing application of probiotics as biotherapeutics, the chapter also discusses some of the emerging techniques for microencapsulation of probiotic strains.
KIIT School of Civil Engineering
1. Dora, N., Nanda, P. and Reddy, N. G. (2021), Application of Biopolymers for Enhancing Engineering Properties of Problematic Soils and Industrial Wastes: A Review in Advances in Sustainable Construction Materials. Lecture Notes in Civil Engineering, S. Biswas, S. Metya, S. Kumar, and P. Samui (Eds.), Springer, Singapore, Vol. 124, pp. 203-211.
Abstract: Stabilization of materials using cement and lime is a widespread practice for the improvement of engineering properties. Due to the negative impacts of these additives on the environment, there is an increasing focus on the use of sustainable and eco-friendly additives for improving the strength or engineering properties. In this study, an attempt is made to review the application of biopolymers to enhance the engineering properties of problematic soil and waste materials. This review shows that biopolymers exhibit great promise in improving strength, reducing permeability, and alleviating problematic soil and waste material challenges in a sustainable manner.
2. Pati, S., Jena, B. and Sahoo, K. K. (2021), Mechanical Properties and Chloride Content on Self-compacting Concrete Exposed to Sea Water, in Advances in Sustainable Construction Materials. Lecture Notes in Civil Engineering, S. Biswas, S. Metya, S. Kumar, P. Samui (Eds.), Springer, Singapore, Vol. 124, pp. 461–474.
Abstract: The study evaluated the strength and chloride content of marine self-compacting concrete using silica fume and silpozz as partial replacement to Ordinary Portland Cement (OPC). M30 concrete is prepared where, based on several trial mixes, the amount of water is reduced by 25%, but there is no change for the quantity of materials in OPC concrete. The mechanical properties like compressive strength, flexural strength, and split tensile strength has been studied. Results showed Self Compacting Concrete (SCC) containing 5% silica fume and 10–20% silpozz with doses of super plasticizer have less than 5% deterioration factor of compressive strength. The pre-cast blended SCC samples exhibited the best performance.
KIIT School of Computer Engineering
1. Pravind U., Porwal P., Sahoo A.K., Pradhan C. (2021), Collaborative Filtering-based Robust Recommender System using Machine Learning Algorithms in Recommender Systems, Kumar, P.P., Vairachilai, S., Potluri, S., and Mohanty, S.N. (Eds.), CRC Press, Boca Raton, pp.1-21.
Abstract: The boom in e-commerce sites and online businesses increases the need for a robust recommendation system. To predict the correct product and recommend the relevant product to the unknown user, we use collaborative filtering-based robust recommender system. This chapter reviews some of the different machine learning algorithms used in the recommendation system and also offers a brief comparison study of different machine learning algorithms. Our main focus is to build an efficient and robust recommender system which provides a high degree of predictive accuracy and a better standard of recommendation.
2. Patra S. S., Harshvardhan G. M., Gourisaria M. K., Mohanty J. R., Choudhury S. (2021), Emerging healthcare problems in High-Dimensional Data and Dimension Reduction, Advanced Prognostic Predictive Modelling in Healthcare Data Analytics, Lecture Notes on Data Engineering and Communications Technologies, Roy, S., Goyal, L.M., and Mittal, M. (Eds.), Springer, Singapore, Vol 64, pp. 25-49, https://doi.org/10.1007/978-981-16-0538-3_2.
Abstract: Due to new and emerging technologies in the medical sector, we see a stark augment in increase of parameters that model the well-being of human beings. These huge amounts of data lead to the formation of diverse clinical datasets. These clinical datasets are analyzed mathematically, and relationships are found using data mining to perform the regression, classification, or clustering-based tasks. However, with the increasing diversity of clinical datasets, the problem of data redundancy arises. Here we discussed the PCA, t-SNE, SVD, and LDA algorithms for dimensionality reduction and its implementation into the area of high-dimensional healthcare data to lower dimension.
3. Mishra A., Gourisaria M. K., Gupta P., Patra S. S., Barik L. B. (2021), Model Based Filtering Systems Using a Latent Factor Technique, Recommender Systems: Algorithms and Applications (1st ed.), Kumar, P.P., Vairachilai, S., Potluri, S., and Mohanty, S.N. (Eds.), CRC Press. https://doi.org/10.1201/9780367631888.
Abstract: Recommender systems have become increasingly prevalent in our lives, with the ascent of websites such as YouTube, Amazon, and Netflix A common system to give input is as appraisals in which a particular assessment framework is used where clients select numerical qualities from which they indicate their preferences for different things with just one mouse-click. The fundamental thought of the recommender system is to use these different wellsprings of items to induce client intrigues. On the bases of past collaboration among the users and products and their past intrigues and preferences, suggestion examinations or recommendations can be founded.
4. Acharya B., Gupta R., Sahoo P. K., Rout J. K., Ray, N. (2021), Edge of Things-Based Smart Speed Monitoring System: A Smart City Initiative, In Advances in Electronics, Communication and Computing, Springer, Singapore, pp. 75-83.
Abstract: The paper describes an Edge of Things-based vehicle speed monitoring system that could be helpful in realizing the smart city. The proposed model collects information from the various environments of the traffic system. These collected data send to the central control room for processing. This whole process is controlled through a microcontroller unit (MCU). The proposed model also incorporated with a radar system that gauges vehicle speed through the installed surveillance system. Upon exceeding the speed, the vehicles can be traced through different properties and action can be taken accordingly.
5. Patra S. S., Goje N. S., Singh K. N., Khan K. Q., Kumar D., Sharma K. A. (2021), Future of Telemedicine with ML: Building a Telemedicine Framework for Lung Sound Detection, Machine Learning for Healthcare Applications, pp. 323-341.
Abstract: Telemedicine is the supplementary service in the field of medical science related to medical information sharing tool. With the advancements and popularity of machine learning (ML) in several fields of the society, the study in the field of medicine has also geared up and researchers are working in the area of telemedicine to improve its capabilities and procedures to solve specific problems. The combination of ML and telemedicine will give the endless possibilities in the healthcare industry. The goal is to construct a framework by examining the lung sound to predict respiratory issues. The proposed framework is trained through ensemble techniques.
6. Patra S. S., Jena O. P., Kumar G., Pramanik S., Misra C., Singh K. N. (2021), Random Forest Algorithm in Imbalance Genomics Classification, Data Analytics in Bioinformatics: A Machine Learning Perspective, pp. 173-190.
Abstract: Random Forest (RF) is a well-known ensemble technique based on decision tree designed to improve the accuracy of CART and can be applied for classification as well as regression problems. It can be applied to problems which are classified as “large p and small n” problems with highly data adaptive. It accounts the interaction among the features and correlation among features. It works by constructing many CART trees on the training dataset making the model less interpretable. This chapter describes and shows the usefulness of RF algorithm for high dimensional genomic data analysis and shows the accuracy of the result.
7. Chatterjee P. S., Detection of Node Cloning Attack in WSN to Secure IoT-based Application: A Systematic Survey in IoT Applications, Security Threats, and countermeasure, Nayak, P., Ray, N., and Ravichandran, P. (Eds.), CRC Press, India.
Abstract: Independent Wireless Sensors (IWS) are the basis of Wireless Sensor Network(WSN). The recent IWS technologies enable us to develop a vast range of IoT-based applications starting from military to education. The success of these applications largely depends on the reliability of WSNs working behind. But unfortunately there exist many security threats in traditional WSNs which impact the IoT applications. The node-cloning attack is one of such major security threat for WSNs. The network will have many clones of the victim node when there is a presence of node cloning attacker and ….
8. Mukherjee P., Pradhan C. (2021), Blockchain 1.0 to Blockchain 4.0 – The Evolutionary Transformation of Blockchain Technology in Blockchain Technology: Applications and Chalenges, Panda, S.K., Jena, A.K., Swain, S.K., and Satapathy, S.C. (Eds.), Springer, Cham, pp. 29-49.
Abstract: This chapter first gives the historical background of this expeditious technology. It then proffers a description of the basic terminologies in blockchain, it’s types, basic structure of block and different consensus models popularly known. The prime emphasis of this chapter is to bestow an extensive study of the chronological evolutions in Blockchain Technology by highlighting the nitty-gritty of each generation in detail. It also illustrates a parameter wise differences amidst the several generations in terms of their principle areas, consensus models used, utility of smart contracts, the energy and cost requirements and execution speed and scalability.
9. Pravind U., Porwal P., Sahoo A. K., Pradhan C. (2021), Collaborative Filtering-based Robust Recommender System using Machine Learning Algorithms in Recommender Systems Algorithms and Applications, Kumar, P.P., Vairachilai, S., Potluri, S., and Mohanty, S.N. (Eds.), CRC Press, Boca Raton, pp. 1-21.
Abstract: Recommender systems are information-filtering systems that address information overload based on user preferences from large amount of information collected. Today, there is large number of platforms available on the internet which allows users to give their feedback, ratings, and reviews about the items. To predict and recommend the relevant product to the unknown user, we use collaborative filtering-based robust recommender system. This chapter offers a brief comparison study of different machine learning algorithms. Our main focus is to build an efficient and robust recommender system which provides a high degree of predictive accuracy and a better standard of recommendation.
10. Raj S., Singh S., Kumar A., Sarkar S., Pradhan, C. (2021), Feature Selection and Random Forest Classification for Breast Cancer Disease in Data Analytics in Bioinformatics: A Machine Learning Perspective, Satapathy, R., Choudhury, T., Satapathy, S., Mohanty, S.N., and Zhang, X. (Eds.), Wiley, pp. 191-210.
Abstract: Breast Cancer is one of the most typical type of disease which occurs in women. We have discussed the techniques and mathematics behind some algorithms used in machine learning and how that can help in detection of Breast Cancer. Our research aims at determining the features which are mostly responsible for breast cancer. We have used different methods of feature selection for detection of Breast Cancer and further, we have applied Random Forest Classification on our model. We have got a good result and further it can be preferred for the detection of Breast Cancer.
11. Pattnayak P, Panda A. R. (2021),Innovation on Machine Learning in Healthcare Services—An Introduction, Tripathy, H.K., Mishra, S., Mallick, P.K., and Panda, A.R. (Eds.), Springer, Springer Nature Singapore Pte Ltd, pp. 1–30. https://doi.org/10.1007/978-981-33-4698-7.
Abstract: The provision of health care in developed and developing countries is of great importance.The use of machine know-how in healthcare companies has a crucial importance and is rapidly growing.Current Electronic Wellness Records (EWRs) offer clinically relevant information.The measures in EHRs develop prepare human services for the use of the acquisition of gadgets.This chapter discusses the potential of the use of gadget mastering technology in medical care and describes the use of system research initiatives in various industry projects to contribute to the health sector.
12. Pattnayak P., Jena O.P., Sinha S. (2021), Cloud and Green IoT-based Technology for Sustainable Smart Cities, Jena, O.P., Tripathy, A.R., and Polkowski, Z. (Eds.), Taylor & Francis Group, CRC Press, Boca Raton, pp.1-19. https://doi.org/10.1201/9781003176275.
Abstract: The Internet of things (IoT) shows its remarkable impact with the technological development in the intelligent world.IoT is one of the key components of information and communication technology infrastructure in smart, sustainable cities in order to promote environmental sustainability.By identifying contamination with IoT and ecologic sensors, it will make skilled urban communities greener.This chapter addresses the G-IoT configuration which is suggested to highlight the fixation in order to reduce the use of energy at every stage and ensure that IoT is established in the green environment.This G-IoT design is based on a cloud-based system that reduces hardware utilisation.
13. Pattnayak P., Jena O.P. (2021), Innovation on Machine Learning in Healthcare Services–An Introduction, Mohanty, S.N., Nalinipriya, G., Jena, O.P., and Sarkar., A. (Eds.), Wiley, pp 1-15, https://doi.org/10.1002/9781119792611.ch1.
Abstract: The provision of health care in developed and developing countries is of great importance.The use of machine know-how in healthcare companies has a crucial importance and is rapidly growing.The application of machine training in the healthcare industry is multiple and endless.Machine education helps to streamline hospital administrative processes.We will discuss in that chapter how machine learning improves hospital efficiency, health systems through lower health-care costs, improves health information management and shared health information, with the goal of enhancing and modernising workflows, facilitating access to clinical data and enhancing health information accuracy.
14. Chatterjee R., Chatterjee A., Halder R. (2021), Impact of Deep Learning on Arts and Archaeology: An Image Classification Point of View, Proceedings of International Conference on Machine Intelligence and Data Science Applications, Algorithms for Intelligent Systems, Prateek, M., Singh, T.P., Choudhury, T., Pandey, H.M., and Gia, N. N. (Eds.), Springer, Singapore. pp 801-810. https://doi.org/10.1007/978-981-33-4087-9_65.
Abstract: Any civilized society creates arts and monuments to reflect their beliefs and ideas. The human race must preserve these from such damage and illegal means of trade. Photography plays a vital role in monitoring and cataloging such arts and sculptures. To minimize human interventions, an automated deep learning-based image classification technique is an efficient way to discriminate different arts and sculptures. Here, we have used different deep learning-based transfer learning models to classify the Indic, Egyptian, and Italian sculpture images. Our trained models achieve 98.15% and 97.36% accuracies for the aforementioned sculptures and Kaggle datasets, respectively.
15. Chatterjee R., Chatterjee A., Halder R. (2021), An Efficient Pneumonia Detection from the Chest X-Ray Images, Proceedings of International Conference on Machine Intelligence and Data Science Applications, Algorithms for Intelligent Systems, Prateek, M., Singh, T.P., Choudhury, T., Pandey, H.M., and Gia, N. N. (Eds.), Springer, Singapore, pp 779-789, https://doi.org/10.1007/978-981-33-4087-9_63.
Abstract: The human race is experiencing an unprecedented crisis due to the outbreak of the COVID-19 pandemic. Pneumonia is one of the symptoms of severe stages of the infection. X-Ray is the reliable tool for the diagnosis of Pneumonia and its variants. It requires human expertise to conclude the observations from the X-Ray images. An automated solution could be an efficient and reliable alternative. VGG16 & 19, ResNet50, MobileNetV1, and EfficientNetB3 are implemented and compared with one another based on the obtained accuracy. The EfficientNet-B03 provides 93% and 88.78% accuracies for the viral and bacteria variants of chest X-Ray classification, respectively
16. Chatterjee R., Halder R. (2021), Discrete Wavelet Transform for CNN-BiLSTM-Based Violence Detection, Advances in Systems, Control and Automations, Bhoi, A.K., Mallick, P.K., Balas, V.E., and Mishra, B.S.P. (Eds.), Lecture Notes in Electrical Engineering, Springer, Singapore, Vol. 708, pp 41-52, https://doi.org/10.1007/978-981-15-8685-9_4.
Abstract: In this paper, our approach aims to enhance the classification of violent and non-violent activities in public areas. Violent activities lead to the destruction of loss of life and general properties. These anti-social activities have been increasing at an alarming rate over the past years. Our approach, when merged with the camera surveillance system, can bring about real-time automation, in the detection of criminal activities. DWT-based convolutional bidirectional LSTM has been used to detect violent actions, and the results have been compared with the other methods. Our proposed plan gives 94.06% classification accuracy for the widely used standard Hockey dataset.
Abstract: The book explores modern sensor technologies while also discussing security issues, which is the dominant factor for many types of IoT applications. It also covers recent (IoT) applications such as the Markovian Arrival Process, fog computing, real-time solar energy monitoring, healthcare, and agriculture. Fundamental concepts of gathering, processing, and analyzing different Artificial Intelligence (AI) models in IoT applications are covered along with recent detection mechanisms for different types of attacks for effective network communication. On par with the standards laid out by international organizations in related fields, book focuses on both core concepts of IoT along with major application areas.
KIIT School of Computer Engineering
Jena S., Sahu P. K., Mohapatra S.K. (2021), Efficient Wireless Power Transfer System for Biomedical Applications in Electronic Devices, Circuits, and Systems for Biomedical Applications, Tripathi, S,L., Balas, V.E., Mohapatra, S.K., Prakash, K.B., and Nayak, J. (Eds.), Elsevier, Academic Press, pp. 405–422.
Abstract: Current ultra-low-power biomedical instruments possess a wireless power transfer system using an inductive link, which provides an increasingly attractive method to deliver power to biomedical implants safely. Biomedical implanted devices are becoming popular in a wide range of areas, such as cardiac pacemakers, retinal prosthesis, cochlear implants, defibrillators, smart orthopaedic implants, artificial hearts, etc. The system consists of two primary coils, such as a transmitter coil placed at the outside of the human body and receiver coil placed inside the body. A brief design has been suggested for evaluating the performance of the inductive link with high transmission efficiency.