Engineering a low-cost diatomite with Zn-Mg-Al Layered triple hydroxide (LTH) adsorbents for the effectual removal of Congo red: Studies on batch adsorption, mechanism, high selectivity, and desorption
Adsorption; Congo red; Diatomite; Modification; Removal; Zn-Mg-Al LTH
In this work, naturally occurring, low-cost diatomite (De) or diatomaceous earth (DE) adsorbent was treated with various molar concentrations (0.05, 0.1, and 0.2 M) of Zn-Mg-Al layered triple hydroxide (LTH) using a co-precipitation approach. The DE-modified samples were named 0.05 LDE, 0.1 LDE, and 0.2 LDE and employed to remove Congo Red (CR) dye from an aqueous solution. The adsorbents were examined using XRD, BET-N2 adsorption-desorption method, ATR-IR, FESEM-EDX, and XPS, and also analyzed for zeta potentials of adsorbents at pH values between 5 and 11 to observe their surface charges. The removal efficiencies of CR were 96.5%, 99.7%, and 94.5% for 20 mg of 0.05 LDE, 0.1 LDE, and 0.2 LDE, respectively, at pH 7. A bare DE, however, showed a removal efficiency of only 7.4%. After CR adsorption, the maximum adsorption capacities (qmax) of the adsorbents were examined using the Langmuir isotherm, and the results showed that 0.1 LDE-CR (44.0 mgg?1) had a higher qmax than 0.05 LDE-CR (35.6 mgg?1), 0.2 LDE-CR (27.9 mgg?1), and DE-CR (0.9 mgg?1). The optimal adsorbent of 0.1 LDE was utilized for the selectivity and salt effects based on the investigation's efficiency in removing contaminants. 0.1 LDE has been studied for reusability of up to five cycles and can remove CR up to three cycles with 77.7% and 79.9% efficiency using NaCl and NaOH, respectively. The adsorbents may therefore be particularly effective at removing CR from water and beneficial in industrial settings where dye is often used. 2023 Elsevier B.V.
Vishal K.; Aruchamy K.; Sriram G.; Ching Y.C.; Oh T.H.; Hegde G.; Ajeya K.V.; Joshi S.; Sowriraajan A.V.; Jung H.-Y.; Kurkuri M.
Colloids and Surfaces A: Physicochemical and Engineering Aspects, Vol-661
https://doi.org/10.1016/j.colsurfa.2023.130922 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146288743&doi=10.1016%2fj.colsurfa.2023.130922&partnerID=40&md5=0caef279ba88ff63c542b4d88eed3960
Vishal K., Department of Mechanical Engineering, The National Institute of Engineering, Karnataka, Mysuru, 570008, India, Centre for Research in Functional Materials (CRFM), JAIN (Deemed-to-be-University), Jain Global Campus, Karnataka, Bengaluru, 562 112, India; Aruchamy K., School of Chemical Engineering, Yeungnam University, Gyeongsan, 38541, South Korea; Sriram G., School of Chemical Engineering, Yeungnam University, Gyeongsan, 38541, South Korea; Ching Y.C., Department of Chemical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia; Oh T.H., School of Chemical Engineering, Yeungnam University, Gyeongsan, 38541, South Korea; Hegde G., Centre for Advanced Research and Development (CARD), CHRIST (Deemed-to-be-University), Hosur Rd, Bhavani Nagar, S.G. Palya, Bangalore 29, Karnataka, India; Ajeya K.V., Department of Environment and Energy Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju, 61186, South Korea; Joshi S., Department of Mechanical Engineering, The National Institute of Engineering, Karnataka, Mysuru, 570008, India; Sowriraajan A.V., Fire and Combustion Research Centre, JAIN (Deemed-to-be-University), Jain Global Campus, Karnataka, Bengaluru, 562112, India; Jung H.-Y., Department of Environment and Energy Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju, 61186, South Korea; Kurkuri M., Centre for Research in Functional Materials (CRFM), JAIN (Deemed-to-be-University), Jain Global Campus, Karnataka, Bengaluru, 562 112, India
Engineering applications of artificial intelligence
Artificial intelligence (AI) has evolved rapidly over the past few decades, permeating various aspects of our lives and transforming industries. This chapter explores the emerging applications of AI across diverse fields, including healthcare, finance, transportation, education, and entertainment. In healthcare, AI is revolutionizing diagnostics, drug discovery, personalized medicine, and patient care. In finance, AI-powered algorithms are enhancing trading strategies, risk assessment, fraud detection, and customer service. The transportation sector is witnessing advancements in autonomous vehicles, traffic management, and logistics optimization through AI technologies. AI is also reshaping education with adaptive learning platforms, personalized tutoring, and educational analytics. Moreover, in the entertainment industry, AI is driving content creation, recommendation systems, and virtual experiences. Despite the remarkable progress, challenges such as ethical concerns, bias mitigation, data privacy, and regulatory frameworks need to be addressed for the responsible deployment of AI. 2024, IGI Global. All rights reserved.
Lakkshmanan A.; Seranmadevi R.; Sree P.H.; Tyagi A.K.
Enhancing Medical Imaging with Emerging Technologies, pp. 166-179.
Lakkshmanan A., Department of Computing Technologies, SRM Institute of Science and Technology, Kattankaluthur, India; Seranmadevi R., Department of Professional Studies, Christ University, Bangalore, India; Sree P.H., ECE Department, CVR College of Engineering, Hyderabad, India; Tyagi A.K., Department of Fashion Technology, National Institute of Fashion Technology, New Delhi, India
Engineering applications of blockchain in this smart era
The advent of blockchain technology has revolutionized various industries, offering novel solutions to age-old problems. In this smart era, characterized by interconnected devices and burgeoning digital ecosystems, blockchain stands out as a transformative force. This chapter explores the emerging applications of blockchain technology in this paradigm shift towards smart systems. One prominent application of blockchain lies in the domain of decentralized finance (DeFi). Blockchain facilitates peer-to-peer transactions, eliminating the need for intermediaries like banks. Smart contracts, powered by blockchain, automate and execute agreements, enabling programmable finance, lending, and asset management. Moreover, blockchain's transparency and immutability enhance trust in financial transactions, fostering financial inclusion and security. In the realm of SCM, blockchain offers unprecedented transparency and traceability. By recording every transaction on an immutable ledger, blockchain enables users to track the journey of products from raw materials to end consumers. 2024, IGI Global. All rights reserved.
Tyagi A.K.; Kumari S.; Chidambaram N.; Sharma A.
Enhancing Medical Imaging with Emerging Technologies, pp. 180-196.
Tyagi A.K., National Institute of Fashion Technology, New Delhi, India; Kumari S., SRM Institute of Science and Technology, Chennai, India; Chidambaram N., Department of Professional Studies, Christ University, Bangalore, India; Sharma A., Sharda University, Greater Noida, India
Engineering CoMn2O? nanofibers: Enhancing one-dimensional electrode materials for high-performance supercapacitors
Electrospinning; Nanofibers; One dimensional; Supercapacitor; Symmetric device
One-dimensional CoMn2O4 nanofibers were developed via the electrospinning method, offers a novel approach for designing electrode materials for energy storage device -supercapacitors. Field emission scanning electron microscopy (FESEM) with EDX confirmed the highly porous CoMn2O4 phase with desired composition. Elemental mapping studies confirmed uniform distribution of Co, Mn, and O elements throughout the nanofibers.Electrochemical studies underscored the crucial role of structural voids and spacing in enhancing energy storage capacity, establishing CoMn2O4 as a promising electrode material. Specific energy and power studies yielded remarkable results of 93.84 Whr/kg and 55.20 kW/kg, respectively. Additionally, specific capacitance determination returned 937.42 F/g, indicating exceptional charging and discharging performance over 1000 cycles with 93.3 % capacitance retention. Moreover, the flexible symmetric supercapacitor is expected to demonstrate exceptional flexibility and electrochemical stability, achieving a specific energy of 232 Wh/kg and a specific power of 84 kW/kg at a current density of 1 mA/cm. These findings advance our understanding of CoMn2O4 nanofibers and offer insights into developing efficient and stable energy storage systems for diverse applications. 2025 Elsevier B.V.
Jirankalagi S.N.; Molane A.C.; Sutar S.M.; Mulik R.N.; Selvaraj M.; Sunajadevi K.R.P.; Patil V.B.
https://doi.org/10.1016/j.synthmet.2025.117836 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215929236&doi=10.1016%2fj.synthmet.2025.117836&partnerID=40&md5=4144140e641120d0237c3e72a3bf8670
Jirankalagi S.N., Functional Materials Research Laboratory, School of Physical Sciences, PAH Solapur University, MS, Solapur, 413255, India, Department of Physics, DBF Dayanand College of Arts & Science, MS, Solapur, 413002, India; Molane A.C., Functional Materials Research Laboratory, School of Physical Sciences, PAH Solapur University, MS, Solapur, 413255, India; Sutar S.M., Functional Materials Research Laboratory, School of Physical Sciences, PAH Solapur University, MS, Solapur, 413255, India; Mulik R.N., Department of Physics, DBF Dayanand College of Arts & Science, MS, Solapur, 413002, India; Selvaraj M., Central Labs, King Khalid University, Abha, AlQura'a, P.O. Box 960, Saudi Arabia, Department of Chemistry, Faculty of Science, King Khalid University, Abha, 61413, Saudi Arabia; Sunajadevi K.R.P., Department of Chemistry, Christ University, Karnataka, Bangalore, 560029, India; Patil V.B., Functional Materials Research Laboratory, School of Physical Sciences, PAH Solapur University, MS, Solapur, 413255, India
Jirankalagi, Sidraya N.; Molane, Avinash C.; Sutar, Sarjerao M.; Mulik, Ramesh N.; Selvaraj, Manickam; Sunajadevi, Kalathiparambil Rajendra Pai; Patil, Vikas B.
Synthetic Metals;Volume;311;Issue;;Article No.;117836;
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1016/j.synthmet.2025.117836 https://www.scopus.com/pages/publications/85215929236?origin=resultslist
Engineering Ru(ii) Schiff base complexes as biofunctional materials: cytotoxic and cell imaging perspectives
Four bromine-substituted Ru(ii)-arene Schiff base complexes derived from bromo-picolinaldehyde and 3-(1H-pyrazol-1-yl)propan-1-amine were examined for their cytotoxic behaviour toward cervical cancer (SiHa) and normal fibroblast (3T3-L1) cells using MTT-based in vitro assays. The ligands and complexes were comprehensively characterized by FTIR; 1H, 13C, and 19F NMR; and ESI-LCMS analyses. Single-crystal X-ray diffraction (SCXRD) confirmed the molecular structure of complex 3, while PXRD validated the crystalline nature of complexes 2 and 4. Density functional theory (DFT) calculations further supported the experimental data by revealing optimized geometries and key electronic descriptors. All complexes exhibited time- and dose-dependent anticancer effects, with complexes 24 showing the greatest cytotoxicity toward the SiHa cells (viability at 72 h: 20% 3%, 31% 3%, and 29% 3%, respectively) while maintaining high viability in normal fibroblasts (>90%). The IC50 values for complexes 14 were 19.54 2, 14.21 4, 12.43 4, and 12.43 4 M, respectively. Acridine orange (AO) and ethidium bromide (EtBr) staining and morphological analyses confirmed apoptosis as the primary mechanism of cell death, as evidenced by reduced adhesion, membrane blebbing, and cell rounding. The pronounced and selective cytotoxicity of these bromine-substituted Ru(ii) complexes highlights their potential as promising biomaterial candidates for targeted anticancer therapy. This journal is The Royal Society of Chemistry and the Centre National de la Recherche Scientifique, 2026
Bhunya, Debasis; Datta, Riya; Maity, Swapan; Sahoo, Subhasish; Samanta, Bidhan Chandra
New Journal of Chemistry;Volume;50;Issue;12;pp.5266-5276
https://doi.org/10.1039/d6nj00553e https://www.scopus.com/pages/publications/105032238479?origin=resultslist
Bhunya D., Department of Chemistry, Christ University, Hosur Road, Karnataka, Bengaluru, 560029, India; Datta R., Department of Chemistry, Christ University, Hosur Road, Karnataka, Bengaluru, 560029, India; Maity S., School of Materials Science and Technology, Indian Institute of Technology (IIT), BHU, Varanasi, India; Sahoo S., Department of Chemistry, National Institute of Technology, Rourkela, 769008, India; Samanta B.C., Department of Chemistry, Mugberia Gangadhar Mahavidyalaya, Bhupatinagar, Purba Medinipur, West Bengal, India
Engineering the functionality of porous organic polymers (POPs) for metal/cocatalyst-free CO2 fixation at atmospheric conditions
Atmospheric pressure; CO2 utilization; Cyclic carbonates; Metal/Co-catalyst-free fixation; Porous Organic Polymer (POP)
Carbon dioxide (CO2) utilization as C1 feedstock under metal/co-catalyst-free conditions facilitates the development of eco-friendly routes for mitigating atmospheric CO2 concentration and producing value-added compounds. In this regard, herein, we designed a bifunctional porous organic polymer (POP-1) by incorporating acidic (-CONH) and CO2-philic (-NH/N) sites by judicious choice of organic precursors. Indeed, POP-1 exhibits high heat of interaction for CO2 (40.2 kJ/mol) and excellent catalytic performance for transforming carbon dioxide to cyclic carbonates, a high-value commodity chemical with high selectivity and yield under metal/cocatalyst/solvent-free atmospheric pressure conditions. Interestingly, an analogous polymer (POP-2) that lacks basic (-NH/N) sites showed lower CO2 interaction energy (31.6 kJ/mol) and catalytic activity than that of POP-1. The theoretical studies further supported the superior catalytic activity of POP-1 in the absence of Lewis acidic metal and cocatalyst. Notably, POP-1 showed excellent reusability with retention of catalytic performance for multiple cycles of usage. Overall, this work presents a novel approach to metal/cocatalyst/solvent-free utilization of CO2 under eco-friendly atmospheric pressure conditions. 2024 Elsevier Ltd
Das R.; Kishan R.; Muthukumar D.; Pillai R.S.; Nagaraja C.M.
Journal of Environmental Chemical Engineering, Vol-12, No. 5
https://doi.org/10.1016/j.jece.2024.113777 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201624684&doi=10.1016%2fj.jece.2024.113777&partnerID=40&md5=51263e616c7d6c0e364261a2f6a335dd
Das R., Department of Chemistry, Indian Institute of Technology Ropar, Punjab, Rupnagar, 140001, India; Kishan R., Department of Chemistry, Indian Institute of Technology Ropar, Punjab, Rupnagar, 140001, India; Muthukumar D., Department of Chemistry, Christ University, Bengaluru, 560 022, India; Pillai R.S., Department of Chemistry, Christ University, Bengaluru, 560 022, India; Nagaraja C.M., Department of Chemistry, Indian Institute of Technology Ropar, Punjab, Rupnagar, 140001, India
English language traning for core course instruction in commerce courses :
Tracing the scope and growth of English in the globalised world, this research focusses on helping the learners to improve their English language proficiency through core course instruction. The research has identified the scope of study in the Commerce discipline of higher education setting. The study aims to locate the possibility of learning and improving general vocabulary for the purpose of communication. It traces the existing studies in integrating English language in core course content at various levels and establishes the gap in the study. The mileage that English Language Teaching has covered in the past few decades is far newlinefrom listing. However, areas of study that might seem familiar and established still newlineseem to provide more scope for research. English language, no doubt has become newlinethe medium of instruction in most of the higher education settings. Students get newlineexposed to different course content through English, and training teachers for various skills has become an important quarter in the education setting. With each passing generation, there is a need to create a training approach that suits the lifestyle, advancements in various forums and needs of the learners. This research attempts to create a training module for the purpose of equipping teachers with the ability to teach English, which is the medium of instruction, through core course instruction in the higher education scenario. The research provides a module that could serve as a model for teachers to use language effectively and equip their learners not just with the knowledge of the subject, but also the knowledge of the language through which the content is delivered. The purpose of this study is to highlight the need for a holistic understanding of the language used for content delivery and also to enable students to be able to use the language inputs received here, in daily life communication too.
English to Hindi Translation System Using Hybrid Techniques
Good communication is critical for overcoming cultural and linguistic divides in today's internationalized society. An essential communication component is the Translation of written materials, primarily academic papers, from one language into another. This abstract focuses on the research involved in translating academic publications from Hindi to English. Translating Hindi academic papers into English is naturally hard due to the significant linguistic and cultural differences between the two languages. The proposed work provided an analytical analysis of various models used in language translation, including the seq-to-seq model, MT5, and LSTM, with the help of BLEU score, Learning rate, and average loss. MT5 model outshines others in terms of an average loss of 4.75; meanwhile, LSTM has an average loss of 5.56, and the seq-to-seq model has an average loss of 6.09, implying weaker Translation. 2024 IEEE.
Proceedings of InC4 2024 - 2024 IEEE International Conference on Contemporary Computing and Communications
Institute of Electrical and Electronics Engineers Inc.
Rajora B., CHRIST (Deemed to be University), Department of Computer Science and Engineering, Bangalore, India; Yogish D., CHRIST (Deemed to be University), Department of Computer Science and Engineering, Bangalore, India; Elappila M., CHRIST (Deemed to be University), Department of Computer Science and Engineering, Bangalore, India
Enhanced AIS Based Intrusion Detection System Using Natural Killer Cells
AIS; anomaly detection; IDS; Intrusion; natural killer cells
Intrusion detection system is used to monitor the system and network activities to identify anomalies and attacks so that integrity, availability, and confidentiality can be preserved. Here an intrusion detection system based on Artificial Immune System is proposed based on Natural Killer (NK) cells with immunological memory. NK cells are created and each NK cells detection radius is determined using the negative selection algorithm and is trained to detect various attacks. Effective cells with high fairness values are proliferated and distributed to the network using clonal selection algorithm. In this paper, two types of NK cell are used-a Heavyweight NK cell (HWNK) and a number of Lightweight NK cells (LWNK). The incoming data is vectorized and Major Histocompatibility Complex Class I (MHC1) is created. Then based on this MHC1, any of the receptors i.e. Activating Receptor or Inhibiting Receptor is activated. If it is the signature of an attack, Activating Receptor is activated. Activating receptor activation results in either cytokine release or apoptosis. Here cytokine release means an alarm is generated informing the administrator and apoptosis stands for dropping of the packet. If Inhibiting Receptor is activated, it's a normal packet there is no action taken. The technique proposed yields high accuracy, better detection rate and quick response time. 2020 River Publishers. All Rights Reserved.
Journal of Cyber Security and Mobility, Vol-9, No. 4, pp. 515-534.
https://doi.org/10.13052/jcsm2245-1439.942 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101229415&doi=10.13052%2fjcsm2245-1439.942&partnerID=40&md5=b1a95e6e267fa550b218b92cbcf63e07
Bejoy B.J., Department of CSE, Christ (Deemed to be University), India; Janakiraman S., Department of Banking Technology, Pondicherry University, India
Enhanced Approach for Precision Agriculture Using AI/ML Techniques
Artificial Intelligence; Data Science; Precision Agriculture; Supervised Learning; Unnamed Aerial Vehicle
Precision-based agriculture has been made possible by recent technical breakthroughs and developments in information technology. These new developments have made it possible to better utilise contemporary methods and instruments, like IOT, soft computing, and wireless sensor technology, to increase the agricultural productions environmental and economic sustainability. Precision farming is a new trend in agriculture that sets itself apart from traditional farming methods by applying resources in a way that is efficient, planned, systematic, and justified in order to produce higher and better yields. Precision farming uses geographic information systems like weather patterns, remote sensing technologies like Wireless Sensor Networks (WSN), and soft computing tools like Support Vector Machines (SVM), Random Forest (RF), Artificial Neural Networks (ANN), and Decision Trees (DT) to monitor and predict farm produce requirements in real time and for the future. This study examines the application of several methods and tools used in precision farming. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Agarwal, Vedant; Budhiraja, Samiksha; Sasi, Ashwin; Jeno Lovesum, S.P.
Lecture Notes in Networks and Systems;Volume;1247 LNNS;pp.19-30
Springer Science and Business Media Deutschland GmbH
https://doi.org/10.1007/978-3-031-81086-2_3 https://www.scopus.com/pages/publications/105005391660?origin=resultslist
Agarwal V., Computer Science and Engineering Bangalore, Christ University, Karnataka, Bengaluru, India; Budhiraja S., Computer Science and Engineering Bangalore, Christ University, Karnataka, Bengaluru, India; Sasi A., Computer Science and Engineering Bangalore, Christ University, Karnataka, Bengaluru, India; Jeno Lovesum S.P., Computer Science and Engineering Bangalore, Christ University, Karnataka, Bengaluru, India
Enhanced Artificial Neural Network for Emoji Sentiment Analysis
Artificial Neural Networks (ANNs); Computational efficiency; Emoji sentiment analysis; He and Xavier initialization; Sentiment classification; Supervised machine learning; Text mining; Weight initialization strategy
Emojis enhance textual communication by conveying emotions and providing contextual richness. This study compares the performance of supervised machine learning models such as Naive Bayes, Logistic Regression, Random Forest, K-Nearest Neighbors (KNN), and Artificial Neural Networks (ANNs) for emoji sentiment classification. A major addition in this study is the enhancement of the ANN model using an informed weight initialization technique, which speeds up convergence and reduces training time while maintaining improved performance. The experimental results showed that the Enhanced ANN (EANN) model obtained 94% accuracy, a 2% improvement over the baseline ANN model, while lowering training time from 45 to 18 units (60% decrease), highlighting the importance of initialization strategies in deep learning. The initialization method helped the EANN network avoid overfitting, resulting in increased generalization and accuracy. Proper initialization balanced the gradients during backpropagation, avoiding gradient issues that limit deep networks. Also, the informed weight initialization guaranteed that the EANN began training closer to an optimal solution, lowering the possibility of becoming confined in suboptimal local minima. The findings from this study contribute to advances in sentiment analysis and text mining, particularly in terms of improving the efficiency and accuracy of deep learning approaches. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
Swetha Cordelia, A.; Kokatnoor, Sujatha Arun; Lamani, Manjunath Ramanna; Das, Shreyashi
Lecture Notes in Networks and Systems;Volume;1672 LNNS;pp.205-217
https://doi.org/10.1007/978-981-95-3492-0_16 https://www.scopus.com/pages/publications/105040568086?origin=resultslist
Swetha Cordelia A., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India; Kokatnoor S.A., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India; Lamani M.R., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India; Das S., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India
Enhanced Autism Prediction using Hybrid Machine Learning Model
Autism; Cross-validation; Deep Learning; Gradient Boosting; Machine Learning
Autism Spectrum Disorder (ASD) is a condition where individuals face challenges in neurological development and have verbal, non-verbal, learning and behavioral disorders. Even though this condition is identifiable in the first few years in the children's life, many remain undiagnosed until later. This leads to long term developmental issues and delayed interventions. This is what makes the early detection critical for improving development in children. Despite that, traditional diagnosis approaches like behavioral checklists and pre structured interviews rely on the clinician's expertise and are time consuming and have a risk of inconsistency. This study entails and addresses the above problem by proposing a machine learning based multi model to automate early detection in toddlers aged 12 to 36 months. In the initial stage, the traditional classification algorithms like Logistic Regression, SVM are evaluated with high accuracy, F1 score. Then, hybrid models are developed by combining Gradient Boosting as the anchor model with other high performing algorithms, to overcome the limitation of single classification models. These hybrid models help to overcome the limitations of the individual classifiers. Finally, the best-performing hybrid model is enhanced further by Hyperparameter tuning, Feature selection and Cross validation. The outcome of this research will be a hybrid model, combining machine learning algorithms with the best scores, ensuring high accuracy and low false positives. This aims to help in the detection of ASD in early stages in toddlers. 2025 IEEE.
Bhavya, A.; Srivastava, Kamakshi; Jayapandian, N.
2025 IEEE 5th International Conference on ICT in Business Industry and Government, ICTBIG 2025;
https://doi.org/10.1109/ICTBIG68706.2025.11323994 https://www.scopus.com/pages/publications/105032907036?origin=resultslist
Bhavya A., CHRIST (Deemed to Be University), Department of CSE, India; Srivastava K., CHRIST (Deemed to Be University), Department of CSE, India; Jayapandian N., CHRIST (Deemed to Be University), Department of CSE, India
Enhanced Automated Online Examination Portal Using Convolutional Neural Network
Artificial Intelligence; Cloud Computing; Learning Management Systems; Machine Learning; Online Examination; Proctoring Systems
In recent years, the digital evolution of education has significantly shaped the landscape of learning, steering it away from traditional classroom settings towards more agile e-learning platforms. This shift has underscored the urgency for comprehensive online examination systems, tailored to meet the unique challenges and demands of virtual education. Online learning platforms have seen a rapid rise in popularity, given their flexibility, cost-effectiveness, and capability to cater to learners worldwide. Such a widespread audience brings along the challenge of conducting exams without the constraints of geography and scale. Traditional examinations, with their manual paper based formats, fail to fit within this digital mold due to their logistical challenges and inefficiencies. Consequently, an online examination system not only introduces convenience but also operational efficiency, eliminating many of the logistical nightmares associated with manual exams. While existing tools might provide online testing capabilities, the integration of Artificial Intelligent driven proctoring in this portal elevates the standards of academic integrity to unprecedented levels. The main aim of this article is to create online test platform with the support of Artificial Intelligence technology. The result detect the malpractice activity and electronic device usage detection while online examination. 2023 IEEE.
Vivek M.; Clintford P.S.; Prithvi R.; Maurya A.K.; Jayapandian N.
4th International Conference on Communication, Computing and Industry 6.0, C216 2023
Vivek M., Department of CSE, CHRIST (Deemed to be University), India; Clintford P.S., Department of CSE, CHRIST (Deemed to be University), India; Prithvi R., Department of CSE, CHRIST (Deemed to be University), India; Maurya A.K., School of Engineering and Technology, CHRIST (Deemed to be University), India; Jayapandian N., School of Engineering and Technology, CHRIST (Deemed to be University), India
Enhanced Automated Oxygen Level controller for COVID Patient By Using Internet of Things (IoT)
Cloud Computing; Internet of Things; Oxygen Concentration; Peak Detection Algorithm; Smart Pulse Oximeter
The Internet of Things (IoT) shall be merged firmly and interact with a higher number of altered embedded sensor networks. It provides open access for the subsets of information for humankind's future aspects and on-going pandemic situations. It has changed the way of living wirelessly, with high involvement and COVID-related issues that COVID patients are facing. There is much research going on in the recent domain, like the Internet of Things. Considering the financial-economic growth, there isn't much significance as IoT is growing with industry 5.0 as the latest version. The newly spreading COVID-19 (Coronavirus Disease, 2019) will emphasize the IoT based technologies in a greater impact. It is growing with an increase in productivity. In collaboration with Cloud computing, it shows wireless communication efficiently and makes the COVID-19 eradication in a greater way. The COVID-19 issues which are faced by the COVID patients. Many patients are suffering from inhalation because of lung problems. The second wave attacks mainly on the lungs, where there is a shortage of breathing problems because of less supply of oxygen (insufficient amount of oxygen). The challenges emphasized as proposed are like the shortage of monitoring the on-going process. Readily being active in this pandemic situation, the mentioned areas are from which need to be discussed. The frameworks and services are given the correct data and information for supply of oxygen to the COVID patients to an extent. The Internet of Things also analyzes the data from the user perspective, which will later be executed for making on-demand technology more reliable. The outcome for the COVID-19 has been taken completely to help the on-going COVID patients live, which can be monitored through Oxygen Concentration based on the IoT framework. Finally, this article discusses and mentions all the parameters for COVID patients with complete information based on IoT. 2022 IEEE.
Karmakar A.; Mohan T.L.R.; Jayapandian N.
6th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2022 - Proceedings, pp. 465-470.
Karmakar A., Christ (Deemed to Be University), Department of Cse, India; Mohan T.L.R., Christ (Deemed to Be University), Department of Cse, India; Jayapandian N., Christ (Deemed to Be University), Department of Cse, India
Enhanced Battery Life with Supercapacitor Applied to Renewable Energy Based Electric Vehicles
Electric vehicles (EVs); Fuzzy logic controller (FLC); Hybrid energy storage system (HESS); Math Function-Based (MFB) Controller; Proportional-Integral (PI) controller; Solar power
The main goal of this work is of developing a control approach, which is able to obtain the smooth switching between energy sources, battery, and Supercapacitor (SCAP). With four separate math functions, a new math function-based (MFB) controller is designed, and this MFB will generate four output signals corresponding to the motor's speed. Further, the MFB is combined with an FLC/PI controller to reach the theme of the work. Two-hybrid different controllers are intended as per the proposed control strategy termed as MFB with FLC and MFB with PI and both are implemented individually in MATLAB/Simulink in four different modes. The entire model is implemented including a solar panel to charge the battery, this solar panel (SP) is connected to the battery and UDC through various control switches. Finally, a comparative analysis is made between two hybrid controllers to know the better-performed controller. 2023 Ecole Polytechnique de Montreal. All rights reserved.
Journal of New Materials for Electrochemical Systems, Vol-26, No. 3, pp. 164-171.
International Information and Engineering Technology Association
https://doi.org/10.14447/jnmes.v26i3.a04 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174075280&doi=10.14447%2fjnmes.v26i3.a04&partnerID=40&md5=e4860e550facb2eaebb7d3e694cd9852
Katuri R., Department of Electrical engineering, VFSTR Deemed to be University, Vadlamudi, Guntur, 522213, India; Kumar S.L.V.S., ZF Technology Center Hyderabad, India; Suresh K., Christ - Deemed to be University, Karnataka, Bengaluru, 560029, India
Enhanced Channel Division Method for Estimation of Discharge in Meandering Compound Channel
Apparent shear force; Channel division method; Discharge; Gene-expression programming; Interface method; Meandering compound channel; Percentage of shear force
Accurate prediction of shear force distribution along the boundary in open channels is a key to the solution of numerous hydraulic problems. The problem becomes more complicated for meandering compound channels. A model is developed for predicting the percentage of shear force at the floodplain (%Sfp) of two-stage meandering channels using gene-expression programming (GEP) by considering five dimensionless parameters viz. the width ratio, relative depth, sinuosity, bed slope, and meander belt width ratio as the inputs in the model. Basing on the %Sfp, the apparent shear force along the division lines of separation in compound channels is selected for discharge calculation using the conventional channel division methods. An Enhanced Channel Division Method (ECDM) is introduced to calculate discharge by assuming interface line at main channel and floodplain junction. A modified variable-inclined (MVI) interface is suggested having zero apparent shear determined from flow contribution in the main channel and floodplain. The MVI interface is further used to calculate discharge in the meandering compound channels. Performance of the GEP model is tested against other analytical methods of calculating %Sfp. Error between the observed and calculated discharges using the MVI interface is found to be the minimum when compared to other interface methods. The enhance channel division method is successfully applied for validating the two available overbank discharge values for the river Baitarani at Anandapur (drainage area of 8570 sq. km), giving the minimum errors of 0.31% and 1.02% for flow depths of 7.5m and 8.63m, respectively. 2020, Springer Nature B.V.
Water Resources Management, Vol-34, No. 3, pp. 1047-1073.
https://doi.org/10.1007/s11269-020-02482-y https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077716830&doi=10.1007%2fs11269-020-02482-y&partnerID=40&md5=55de288ca53b2da5029ea01bb3ce76ae
Mohanta A., School of Mechanical Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India; Patra K.C., Department of Civil Engineering, NIT, Rourkela, 769008, Odisha, India; Pradhan A., Department of Civil Engineering, CHRIST University, Bengaluru, 560029, Karnataka, India
Enhanced Cloud Security: Certificateless Public Auditing Using LBMHT for Malicious TPA Detection
AES; CPU; CSP; FEC; IHT; KGC; LBMHT; PDP; RSA; TPA
Leveraging the Lattice-Based Merkle Hash Tree (LBMHT), the paper presents a certificate-less publicly auditing technique that targets hostile third-party auditors (TPAs) in cloud settings. Without the usual burden of certificate-heavy and certificate-management-prone identity-based or encrypted with public keys structures, this method seeks to improve information safety and integrity. To enhance the effectiveness of the Key Generation Centre (KGC), decrease complexity of space, and optimise storage in the cloud, the suggested solution utilises multi-ciphertext searching using lattice-based, certificate-less verification. The concept guarantees collision-free hashes by using a Merkle Tree structure, which makes it effective for information confirmation. Based on simulation findings, LBMHT is superior to current AES and RSA methods in terms of performance, decreasing executions, encryption, and decryption durations while simultaneously decreasing communication expenses, responding duration, and memory utilisation. The suggested approach is more economical with resources and works well in scaled cloud settings because of its increased accuracy, less effect from malevolent attackers, and improved throughput. At the end of the section, we go over the benefits of the framework, which include reduced utilisation of resources and validated indicators of performance. Compared to Rivest-Shamir-Adleman (RSA) and Advanced Encryption Standard (AES), the suggested LBMHT method has a higher overall accuracy of 99.4 percent. The efficiency of LBMHT in securely organising and analysing data is shown by its great accuracy. 2026 American Institute of Physics Inc.. All rights reserved.
Rao, Deepak Dasharatha; Kavitha; Shukla, Prashant Kumar; Tuteja, Disha; Mandal, Pawan; Sinha, Anurag
AIP Conference Proceedings;Volume;3398;Issue;1;Article No.;40001;
https://doi.org/10.1063/5.0319724 https://www.scopus.com/pages/publications/105031734277?origin=resultslist
Rao D.D., TX, United States; Kavitha, Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Shukla P.K., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, K L Deamed to be University, Guntur, Andhra Pradesh, Vaddeswaram, 522302, India; Tuteja D., Department of Electronics and Communication Engineering (ECE), College Guru Tegh Bahadur Institute of Technology, Delhi, India; Mandal P., Department of Forensic Science, RIMT University, Gobindgarh, Punjab, Mandi, 147301, India; Sinha A., School of Computing and Information Science, IGNOU, New Delhi, India
Enhanced Data Security Architecture in Enterprise Networks
Cloud computing; Data cleaning; Data security; Distributed computing; Encryption; Enterprise network; Hadoop file system; Noisy data
Encryption and storing important information is one of the risky and most challenging tasks. It is the need of the hour in todays fast growing technological transformations that the world is undergoing. A simple Enterprise network is the communication backbone of any organization. It mostly provides better information storage and efficient retrieval, which helps the organization to function smoothly, without having to think twice about their crucial datas security aspects. The information technology paradigm, cloud computing is used to help the organization to focus on its core business. In cloud computing is dealing with many services. That service is used for provide Platform service with infrastructure and software service. This paper, promotes the idea of combining various security and encryption algorithms to connect different enterprise networks using cloud computing, security layer concepts and giving no room for hackers to intrude into the confidential system of data. Springer Nature Switzerland AG 2020.
Rashmi Shree V.; Antony Z.C.F.; Jayapandian N.
Lecture Notes on Data Engineering and Communications Technologies, Vol-31, pp. 857-864.
Rashmi Shree V., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Antony Z.C.F., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Jayapandian N., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India