Discrete Integrity Assuring Slice-Based Secured Data Aggregation Scheme for Wireless Sensor Network (DIA-SSDAS)
In a wireless sensor network, data privacy with a minimum network bandwidth usage is addressed using homomorphic-based data aggregation schemes. Most of the schemes which ensure the end-to-end privacy provide collective integrity verification of aggregated data at the receiver end. The presence of corrupted values affects the integrity of the aggregated data and results in the rejection of the whole data by the base station (BS) thereby leading to the wastage of bandwidth and other resources of energy constraint wireless sensor network. In this paper, we propose a secured data aggregation scheme by slicing the data generated by each sensor node deployed in layered topology and enabling en route aggregation. Novel encoding of data and hash slices based on child order is proposed to enable concatenation-based additive aggregation and smooth extraction of slices from the aggregate by the BS. Elliptic curve-based homomorphic encryption is adopted to ensure end-to-end confidentiality. To the best of our knowledge, the proposed scheme is the first which facilitates the BS to perform node-wise integrity verification, filter out only the corrupted portion, and implement dynamic query over the received data. Communication- and computation-based performance analysis shows the efficiency of the proposed scheme for varied network sizes. The scheme can resist eavesdropping attack, node compromising attack, replay attack, malleability attack, selective dropping attack, and collusion attack. 2021 D. Vinodha and E. A. Mary Anita.
Wireless Communications and Mobile Computing, Vol-2021
https://doi.org/10.1155/2021/8824220 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111133645&doi=10.1155%2f2021%2f8824220&partnerID=40&md5=e56df5be9f98f4e4fbaabf88bc6b80b6
Vinodha D., Sri Venkateswara College of Engineering, Sriperumbudur, Chennai, India, Anna University, Chennai, India; Mary Anita E.A., CHRIST (Deemed to Be University), Bengaluru, India
A novel multi functional multi parameter concealed cluster based data aggregation scheme for wireless sensor networks (NMFMP-CDA)
Asymmetric privacy homomorphism; Clustering; Data aggregation; Elliptic curve cryptography; Multiple parameters aggregation; Security; Wireless sensor network
Data aggregation is a promising solution for minimizing the communication overhead by merging redundant data thereby prolonging the lifetime of energy starving Wireless Sensor Network (WSN). Deployment of heterogeneous sensors for measuring different kinds of physical parameter requires the aggregator to combine diverse data in a smooth and secure manner. Supporting multi functional data aggregation can reduce the transmission cost wherein the base station can compute multiple statistical operations in one query. In this paper, we propose a novel secure energy efficient scheme for aggregating data of diverse parameters by representing sensed data as number of occurrences of different range value using binary encoded form thereby enabling the base station to compute multiple statistical functions over the obtained aggregate of each single parameter in one query. This also facilitates aggregation at every hop with less communication overhead and allows the network size to grow dynamically which in turn meets the need of large scale WSN. To support the recovery of parameter wise elaborated view from the multi parameter aggregate a novelty is employed in additive aggregation. End to end confidentiality of the data is secured by adopting elliptic curve based homomorphic encryption scheme. In addition, signature is attached with the cipher text to preserve the data integrity and authenticity of the node both at the base station and the aggregator which filters out false data at the earliest there by saving bandwidth. The efficiency of the proposed scheme is analyzed in terms of computation and communication overhead with respect to various schemes for various network sizes. This scheme is also validated against various attacks and proved to be efficient for aggregating more number of parameters. To the best of our understanding, our proposed scheme is the first to meet all of the above stated quality measures with a good performance. 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Vinodha D.; Mary Anita E.A.; Mohana Geetha D.
Wireless Networks, Vol-27, No. 2, pp. 1111-1128.
Vinodha D., Anna University, Chennai, India, CSE, S. A. Engineering College, Chennai, India; Mary Anita E.A., CSE, CHRIST (Deemed to be University), Bengaluru, India; Mohana Geetha D., ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India
Secure biometric authentication with de-duplication on distributed cloud storage
Artificial Intelligence; Cloud computing; Computer Networks and Communications; Computer Vision; Distributed and Parallel Computing; Dynamic speed scaling algorithm; Edge computing; EIoT; Energy; IoT; Security and Privacy
Cloud computing is one of the evolving fields of technology, which allows storage, access of data, programs, and their execution over the internet with offering a variety of information related services. With cloud information services, it is essential for information to be saved securely and to be distributed safely across numerous users. Cloud information storage has suffered from issues related to information integrity, data security, and information access by unauthenticated users. The distribution and storage of data among several users are highly scalable and cost-efficient but results in data redundancy and security issues. In this article, a biometric authentication scheme is proposed for the requested users to give access permission in a cloud-distributed environment and, at the same time, alleviate data redundancy. To achieve this, a cryptographic technique is used by service providers to generate the bio-key for authentication, which will be accessible only to authenticated users. A Gabor filter with distributed security and encryption using XOR operations is used to generate the proposed bio-key (biometric generated key) and avoid data deduplication in the cloud, ensuring avoidance of data redundancy and security. The proposed method is compared with existing algorithms, such as convergent encryption (CE), leakage resilient (LR), randomized convergent encryption (RCE), secure de-duplication scheme (SDS), to evaluate the de-duplication performance. Our comparative analysis shows that our proposed scheme results in smaller computation and communication costs than existing schemes. 2021 M et al. All Rights Reserved.
Vinoth K.M.; Venkatachalam K.; Prabu P.; Almutairi A.; Abouhawwash M.
PeerJ Computer Science, Vol-7, pp. 1-20.
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.7717/PEERJ-CS.569 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112859669&doi=10.7717%2fPEERJ-CS.569&partnerID=40&md5=3346d10a0987add986da7ccd3627309b
Vinoth K.M., Department of Computer Science and Engineering, Anna University, University College of Engineering, Dindigul, Tamilnadu, India; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, Bangalore, Karnataka, India; Almutairi A., School of Mathematics, Unaizah College of Sciences and Arts, Qassim University, Saudi Arabia; Abouhawwash M., Department of Mathematics, Faculty of Science, Mansoura University, Mansoura, Egypt, Department of Computational Mathematics, Science and Engineering (CMSE), Michigan State University, East Lansing, MI, United States
Design and Evaluation of Wi-Fi Offloading Mechanism in Heterogeneous Networks
Generic Algorithm; Heterogeneous Network; Wi-Fi; Wi-Fi Offloading
In recent years, WiFi offloading provides a potential solution for improving ad hoc network performance along with cellular network. This paper reviews the different offloading techniques that are implemented in various applications. In disaster management applications, the cellular network is not optimal for existing case studies because the lack of infrastructure. MANET Wi-Fi offloading (MWO) is one of the potential solutions for offloading cellular traffic. This word combines the cellular network with mobile ad hoc network by implementing the technique of Wi-Fi offloading. Based on the applications requirements the offloading techniques implemented into mobile-to-mobile (M-M), mobile-to-cellular (M-C), mobile-to-AP (M-AP). It serves more reliability, congestion eliminated, increasing data rate, and high network performance. The authors also identified the issue while implementing the offloading techniques in network. Finally, this paper achieved the better performance results compared to existing approaches implemented in disaster management. Copyright 2021, IGI Global.
Vinoth Kumar V.; Ramamoorthy S.; Dhilip Kumar V.; Prabu M.; Balajee J.M.
International Journal of e-Collaboration, Vol-17, No. 1, pp. 62-70.
https://doi.org/10.4018/IJeC.2021010104 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095750101&doi=10.4018%2fIJeC.2021010104&partnerID=40&md5=ed0ebc58b3e74503ceaf7e5b6a73cff4
Vinoth Kumar V., MVJ College of Engineering, Bangalore, India; Ramamoorthy S., Dr. M.G.R. Educational and Research Institute, India; Dhilip Kumar V., Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India; Prabu M., Christ University (Deemed), Bangalore, India; Balajee J.M., Vellore Institute of Technology, India
EPCAEnhanced Principal Component Analysis for Medical Data Dimensionality Reduction
Accuracy; Artificial neural networks; Liver cirrhosis; Machine learning; Medical data; Principal component analysis; Singular value decomposition; Support vector machine
Innovations in technology from thelast one decade have led to the generation of colossal amounts of medical data with comparably low cost. Medical data should be collected with utmost care. Sometimes, the data have high features but not all the features play an important role in drawing the relations to the mining task. For the training of machine learning algorithms, all the attributes in the data set are not relevant. Some of the characteristics may be negligible and some characteristics may not influence the outcome of the forecast. The pressure on machine learning algorithms can be minimized by ignoring or taking out the irrelevant attributes. Reducing the attributes must be done at the risk of information loss. In this research work, an Enhanced Principal Component Analysis (EPCA) is proposed, which reduces the dimensions of the medical dataset and takes paramount care of not losing important information, thereby achieving good and enhanced outcomes. The prominent dimensionality reduction techniques such as Principal Component Analysis (PCA), Singular Value Decomposition (SVD), Partial Least Squares (PLS), Random Forest, Logistic Regression, Decision Tree and the proposed EPCA are investigated on the following Machine Learning (ML) algorithms: Support Vector Machine (SVM), Artificial Neural Networks (ANN), Nae Bayes (NB) and Ensemble ANN (EANN) using statistical metrics such as F1 score, precision, accuracy and recall. To optimize the distribution of the data in the low-dimensional representation, EPCA directly mapped the data to a space with fewer dimensions. This is a result of feature correlation, which made it easier to recognize patterns. Additionally, because the dataset under consideration was multicollinear, EPCA aided in speeding computation by lowering the data's dimensionality and therebyenhancedthe classification model's accuracy. Due to these reasons, the experimental results showed that the proposed EPCA dimensionality reduction technique performed better when compared with other models. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
Vinutha M.R.; Chandrika J.; Krishnan B.; Kokatnoor S.A.
Vinutha M.R., Department of Information Science and Engineering, Malnad College of Engineering, Hassan, 573202, India; Chandrika J., Department of Information Science and Engineering, Malnad College of Engineering, Hassan, 573202, India; Krishnan B., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, 560074, India; Kokatnoor S.A., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, 560074, India
Applying Ensemble Techniques for the Prediction of Alcoholic Liver Cirrhosis
Alcoholic liver disease; Ensemble classifier; Liver cirrhosis; Machine learning; Random forest; Stacked ensemble classifier; XGBoost
More than fifty percent of all liver cognate deaths are caused by alcoholic liver disease (ALD). Excessive drinking over the time leads to alcohol-related steatohepatitis and fatty liver, this in turn can lead to alcoholic liver fibrosis (ALF) and in due course alcohol-related liver cirrhosis (ALC). Detecting ALD at an early stage will reduce the treatment cost to the patient and reduce mortality. In this research, a two-step model is developed for predicting the liver cirrhosis using different ensemble classifiers. Among 41 features recorded during data collection, only 15 features arefound to be effective determinants of the class variable. The proposed stacked ensemble technique for ALD prediction is compared with other ensemble models such as random forest, AdaBoost, and bagging. Through experimentation, it is observed that the proposed model with XGBoost and decision tree as base models and logistic regression as Meta model exhibits prediction accuracy of 93.86%. The prediction accuracy of theproposed stacked ensemble technique is 0.2% better in prediction accuracy and 0.3% reduced error rate in comparison with random forest classifier. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Networks and Systems, Vol-462, pp. 433-445.
Springer Science and Business Media Deutschland GmbH
Vinutha M.R., Department of ISE, Malnad College of Engineering, Hassan, 573201, India; Chandrika J., Department of ISE, Malnad College of Engineering, Hassan, 573201, India; Krishnan B., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Kokatnoor S.A., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India
RADON in GROUNDWATER of MAGADI TALUK, RAMANAGARA DISTRICT in KARNATAKA
Radon is a water-soluble radioactive noble gas produced from the alpha decay of 226Ra in uranium series. Its presence in drinking water and open air increases the risk of lung and intestinal cancers in human beings. In view of this, radon concentration in groundwater and its dose due to inhalation and ingestion to the population of Magadi taluk of Ramanagara district in Karnataka state, India was studied. The groundwater samples were analyzed for radon concentration using emanometry technique. The study showed that the radon concentration in this area varied from 27.4 1.0 to 167.5 3.9 Bq/L and the effective dose ranged from 104.2 2.7 to 636.2 11.0 ?Sv/a. The study also revealed that 95% of the 37 samples studied showed higher radon concentration compared to the UNSCEAR recommendation (40 Bq/L) and all the samples showed higher than the USEPA recommendation (11.1 Bq/L). Ten samples have concentration above the maximum permissible level prescribed by WHO (100 Bq/L). The groundwater samples are found to be slightly alkaline within the permissible limit of Indian Standards. 2018 The Author(s). Published by Oxford University Press. All rights reserved.
Vipin Kumar P.; Gudennavar S.B.; Chandrashekara M.S.; Bubbly S.G.; Hamsa K.S.
Radiation Protection Dosimetry, Vol-183, No. 4, pp. 514-521.
ISSN: 1448420; PubMed ID: 30265363; CODEN: RPDOD
https://doi.org/10.1093/rpd/ncy176 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068858429&doi=10.1093%2frpd%2fncy176&partnerID=40&md5=2c73cf29f0aac128116aa1fd89b5cbc4
Vipin Kumar P., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Gudennavar S.B., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Chandrashekara M.S., Department of Studies in Physics, University of Mysore, Manasagangotri, Mysuru, 570005, India; Bubbly S.G., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Hamsa K.S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Bengaluru, 560029, India
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
Eye blink detection using CNN to detect drowsiness level in drivers for road safety
Convolution neural network; Cross entropy; Deep learning; Dlib; Eye blink; Mobilenet V2; RMSProp
Blinking is a regular bodily function and it is the semiautomatic fast closing of the eyelid. A specific blink is examined by dynamic folding of the eyelid. It is a vital function of the eye which helps in spread of tears across and eliminates irritants from the shallow of cornea. In this research work we made use of convolution neural network, the deep learning concepts and image processing to detect drowsiness level in drivers. To train the blink detection model the mobilenet V2 is used as base. The loss function used for training was RMSprop and the optimizer is binary cross entropy. The dlib facial landmark was exploited to perceive and pre-process the detected faces. The dataset used for the training model is selected from the Xiaoyang Tan of nanjing university of aeronautics and astronautics. Based on the experimental outcome the projected method achieves an accuracy of 97%. The prototype developed serves as a base for further development of this process to achieve better road safety. 2021 Institute of Advanced Engineering and Science. All rights reserved.
Vishesh P.; Raghavendra S.; Jankatti S.K.; Rekha V.
Indonesian Journal of Electrical Engineering and Computer Science, Vol-22, No. 1, pp. 222-231.
Institute of Advanced Engineering and Science
https://doi.org/10.11591/ijeecs.v22.i1.pp159-167 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104192502&doi=10.11591%2fijeecs.v22.i1.pp159-167&partnerID=40&md5=dfd210eefc3173d59c0cd6f6b6295ffd
Vishesh P., Department of Computer Science and Engineering, CHRIST Deemed to be University, India; Raghavendra S., Department of Computer Science and Engineering, CHRIST Deemed to be University, India; Jankatti S.K., Department of Computer Science and Engineering, KSSEM, VTU, India; Rekha V., Department of Computer Science and Engineering, CHRIST Deemed to be University, India
Improvising data security measures using rajan transform
Cyclic; Data security; Dyadic; Graphical inverse; Homomorphic transform; Rajan transform
Data security has always been a concern with the use of a large amount of data in our day-to-day life. There are many methods suggested and presented to secure data during the stages of its preprocessing and post-processing. However, many of them are not following the process of Homomorphism. During the study of Fast Fourier transform (FFT), Hadamard transform (HT) and Rajan transform (RT), this research work encountered a method that uses the cyclic, dyadic and graphical inverse properties of data and encrypts them which makes them homomorphic. This paper is targeting to improvise the data security measures using Homomorphism-based Rajan Transform, a method, which can help in securing data while data processing. The proposed methodology works in such a way that the encrypted data is available for processing without decrypting data into the original form. The performance of the proposed method is described by the efficiency of the algorithm, key size, Block size, and no of rounds required to complete the encryption. It has been found, if we take 512 bits of input data to get 512-bit ciphertext, it takes 9 rounds and generates a 4608-bit key. 2021 Taylor's University. All rights reserved.
Journal of Engineering Science and Technology, Vol-16, No. 6, pp. 4920-4932.
Vishnoi A., University of Petroleum and Energy Studies, Dehradun, India; Sharma D., Christ University, Delhi, India; Prateek M., Dev Bhoomi Uttarakhand University, Dehradun, India
Construct modelling, statistical analysis and empirical validation using PLS-SEM: a step-by-step guide of the analysis procedure
measurement model; partial least square-structured equation modelling; PLS-SEM; smart-PLS; structural model
Partial least square-structured equation modelling (PLS-SEM) is a widely accepted tool for statistical analysis in social science research. The complex architecture of PLS-SEM sometimes makes it difficult for users to understand the taxonomy, nomenclature, or process of statistical analysis. This research study proposes summarising the procedure adopted in PLS-SEM for data analysis. Measurement evaluation and structural model was the subject of discussion, with a focus on the statistical techniques employed. Furthermore, the threshold values corresponding to statistical tools under measurement and structural model were also provided. The inference of these threshold values were also discussed with an eye on improving researchers awareness and understanding. The discussion about the methodology adopted in statistical analysis with the help of PLS-SEM is also reported. Finally, the limitations of the research work were presented, and further study directions were streamlined. 2024 Inderscience Enterprises Ltd.
Vishnoi S.Kr.; Mathur S.; Bagga T.; Singhal A.; Rawal P.; Sharma S.; Yadav R.
International Journal of Data Analysis Techniques and Strategies, Vol-16, No. 2, pp. 162-180.
https://doi.org/10.1504/IJDATS.2024.137877 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191978288&doi=10.1504%2fIJDATS.2024.137877&partnerID=40&md5=520511ce09b2e6a1c7cd26790acf98fd
Vishnoi S.Kr., Department of Marketing, Institute of Management Studies, UP, Ghaziabad, 201009, India; Mathur S., Christ University, Delhi NCR, 201003, India; Bagga T., Faculty of Management, Department of Management Studies, Jamia Millia Islamia, New Delhi, 110025, India; Singhal A., Institute of Management Studies, UP, Ghaziabad, 201009, India; Rawal P., Institute of Management Studies, UP, Ghaziabad, 201009, India; Sharma S., Christ University, Delhi NCR, 201003, India; Yadav R., Amity School of Business, AUUP, 201313, India
A dual-functional rhodamine B and azo-salicylaldehyde derivative for the simultaneous detection of copper and hypochlorite: synthesis, biological applications and theoretical insights
A multifunctional rhodamine derivative containing azo-salicylaldehyde (BBS) was designed and synthesized as a colorimetric and fluorescence turn-on probe for the selective detection of copper cations (Cu2+) and hypochlorite anions (OCl?) in aqueous media. In the presence of Cu2+, the probe BBS exhibited turn-on absorption and fluorescence change at 554 nm and 585 nm, respectively. The binding mechanism of BBS with Cu2+ induces the opening of a spirolactam ring in the rhodamine moiety by the formation of a metal-ligand complex, achieving 10-fold enhancement in fluorescence and quantum yield, along with a binding constant of 1 104 M?1 and a detection limit of 2.61 ?M. Addition of OCl? enhanced the absorbance and fluorescence intensities at 520 nm and 575 nm, respectively. The probe BBS underwent hypochlorite-mediated oxidation, followed by hydrolysis, resulting in the formation of rhodamine B itself, which is detectable by the naked eye via the color and fluorescence enhancement by 11-fold with a high quantum yield and a detection limit of 1.96 ?M. For practical applications, sensor BBS can be used to detect Cu2+ in water samples and on cotton swabs. For biological applications, the interaction of the BBS-Cu(ii) complex with transport proteins such as bovine serum albumin (BSA) and ct-DNA was investigated through UV-vis and fluorescence titration experiments. Additionally, the structural optimization of BBS and the BBS-Cu(ii) complex was demonstrated using DFT, and the interactions of the BBS-Cu(ii) complex with BSA and ct-DNA were analysed through theoretical docking studies. Bioimaging studies were conducted by capturing fluorescence images of BBS with Cu2+ and OCl? in a physiological medium containing living plant tissue using green gram seeds. 2024 The Royal Society of Chemistry.
Vishnu S.; Das A.K.; Bylappa Y.; Nag A.; Dolai M.
Analytical Methods, Vol-16, No. 47, pp. 8164-8178.
https://doi.org/10.1039/d4ay01758g https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208956278&doi=10.1039%2fd4ay01758g&partnerID=40&md5=4083f93d6704fbcc8c8827e2eb243723
Vishnu S., Department of Chemistry, Christ University, Hosur Road, Karnataka, Bangalore, 560029, India; Das A.K., Department of Chemistry, Christ University, Hosur Road, Karnataka, Bangalore, 560029, India; Bylappa Y., Department of Life Science, Christ University, Hosur Road, Karnataka, Bangalore, 560029, India; Nag A., Department of Life Science, Christ University, Hosur Road, Karnataka, Bangalore, 560029, India; Dolai M., Department of Chemistry, Prabhat Kumar College, Purba Medinipur, WB, Contai, 721404, India
Development of a fluorescent scaffold by utilizing quercetin template for selective detection of Hg2+: Experimental and theoretical studies along with live cell imaging
Cell imaging; Cyclic voltammograms; DFT study; Fluorescence; Green gram; Quercetin
Quercetin is an important antioxidant with high bioactivity and it has been used as SARS-CoV-2 inhibitor significantly. Quercetin, one of the most abundant flavonoids in nature, has been in the spot of numerous experimental and theoretical studies in the past decade due to its great biological and medicinal importance. But there have been limited instances of employing quercetin and its derivatives as a fluorescent framework for specific detection of various cations and anions in the chemosensing field. Therefore, we have developed a novel chemosensor based on quercetin coupled benzyl ethers (QBE) for selective detection of Hg2+ with naked-eye colorimetric and turn-on fluorometric response. Initially QBE itself exhibited very weak fluorescence with low quantum yield (? = 0.009) due to operating photoinduced electron transfer (PET) and inhibition of excited state intramolecular proton transfer (ESIPT) as well as intramolecular charge transfer (ICT) within the molecule. But in presence of Hg2+, QBE showed a sharp increase in fluorescence intensity by 18-fold at wavelength 444 nm with high quantum yield (? = 0.159) for the chelation-enhanced fluorescence (CHEF) with coordination of Hg2+, which hampers PET within the molecule. The strong binding affinity of QBE towards Hg2+ has been proved by lower detection limit at 8.47 M and high binding constant value as 2 104 M?1. The binding mechanism has been verified by DFT study, Cyclic voltammograms and Jobs plot analysis. For the practical application, the binding selectivity of QBE with Hg2+ has been capitalized in physiological medium to detect intracellular Hg2+ levels in living plant tissue by using green gram seeds. Thus, employing QBE as a fluorescent chemosensor for the specific identification of Hg2+ will pave the way for a novel approach to simplifying the creation of various chemosensors based on quercetin backbone for the precise detection of various biologically significant analytes. 2024 Elsevier B.V.
Vishnu S.; Maity S.; Maity A.C.; Kumar M.S.; Dolai M.; Nag A.; bylappa Y.; Dutta G.; Mukherjee B.; Kumar Das A.
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, Vol-315
ISSN: 13861425; PubMed ID: 38603957; CODEN: SAMCA
https://doi.org/10.1016/j.saa.2024.124249 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189863505&doi=10.1016%2fj.saa.2024.124249&partnerID=40&md5=e721d77814a4798293a514e3a798ebd0
Vishnu S., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Maity S., Sagardighi Kamada Kinkar Smriti Mahavidyalaya Sagardighi, West Bengal, Murshidabad, 742226, India; Maity A.C., Sagardighi Kamada Kinkar Smriti Mahavidyalaya Sagardighi, West Bengal, Murshidabad, 742226, India; Kumar M.S., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Dolai M., Department of Chemistry, Prabhat Kumar College, Contai, W.B., Purba Medinipur, 721404, India; Nag A., Department of Life Science, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; bylappa Y., Department of Life Science, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Dutta G., School of Medical Science and Technology (SMST), IIT Kharagpur, India; Mukherjee B., School of Medical Science and Technology (SMST), IIT Kharagpur, India; Kumar Das A., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India
A versatile sensor capable of ratiometric fluorescence detection of trace water and turn-on detection of Cu2+ modulating the binding interaction of a Cu(ii) complex with BSA and DNA complemented by docking studies
A fluorescent molecule, pyridine-coupled bis-anthracene (PBA), has been developed for the selective fluorescence turn-on detection of Cu2+. Interestingly, the ligand PBA also exhibited a red-shifted ratiometric fluorescence response in the presence of water. Thus, a ratiometric water sensor has been utilized as a selective fluorescence turn-on sensor for Cu2+, achieving a 10-fold enhancement in the fluorescence and quantum yield at 446 nm, with a lower detection limit of 0.358 ?M and a binding constant of 1.3 106 M?1. For practical applications, sensor PBA can be used to detect Cu2+ in various types of soils like clay soil, field soil and sand. The interaction of the PBA-Cu(ii) complex with transport proteins like bovine serum albumin (BSA) and ct-DNA has been investigated through fluorescence titration experiments. Additionally, the structural optimization of PBA and the PBA-Cu(ii) complex has been demonstrated by DFT, and the interaction of the PBA-Cu(ii) complex with BSA and ct-DNA has been analyzed using theoretical docking studies. 2024 The Royal Society of Chemistry.
Analytical Methods, Vol-16, No. 30, pp. 5263-5271.
https://doi.org/10.1039/d4ay00675e https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200423567&doi=10.1039%2fd4ay00675e&partnerID=40&md5=7a268ed8cd2397bd5624f68ba86208d8
Vishnu S., Department of Chemistry, Christ University, Hosur Road, Karnataka, Bangalore, 560029, India; Nag A., Department of Life Science, Christ University, Hosur Road, Karnataka, Bangalore, 560029, India; Das A.K., Department of Chemistry, Christ University, Hosur Road, Karnataka, Bangalore, 560029, India
Qualitative and quantitative test of digital micromirror device for next generation UV multi-object spectroscopy
DMD; Multi-Object-Spectrograph; UV telescope
The coming decade in astronomy focuses on large wide field imaging and spectroscopic surveys. No wide field imaging facility extends to the UV region, which represents an important window into a wide variety of astrophysical problems. Also, spectroscopy would be essential to understand the physical and chemical properties of several stars, star forming regions and galaxies. Multi object spectroscopy (MOS) would be an efficient way to obtain these parameters for a large number of objects at a much shorter timescale. Digital Micromirror Device (DMD) acts as a programmable slit mask and can be used to achieve this goal in an MOS. This paper discusses different ground tests conducted on DMD to be used for the above said application. Numerical simulations for the diffraction effects on DMD is also carried out and the results are shared in this paper. 2020 SPIE
Vishnu Unni C.; Sriram S.; Valsan V.; Subramaniam A.
Proceedings of SPIE - The International Society for Optical Engineering, Vol-11444
https://doi.org/10.1117/12.2576340 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099282624&doi=10.1117%2f12.2576340&partnerID=40&md5=d02ca08f52bfee3ac778f2be863d7bc4
Vishnu Unni C., Indian Institute of Astrophysics, Bangalore, India; Sriram S., Indian Institute of Astrophysics, Bangalore, India, Christ (Deemed to be University), Bangalore, India; Valsan V., Christ (Deemed to be University), Bangalore, India; Subramaniam A., Indian Institute of Astrophysics, Bangalore, India
Machine Learning with Data Science-Enabled Lung Cancer Diagnosis and Classification Using Computed Tomography Images
data science; disease diagnosis; image processing; Lung cancer; machine learning; predictive models
In recent times, the healthcare industry has been generating a significant amount of data in distinct formats, such as electronic health records (EHR), clinical trials, genetic data, payments, scientific articles, wearables, and care management databases. Data science is useful for analysis (pattern recognition, hypothesis testing, risk valuation) and prediction. The major, primary usage of data science in the healthcare domain is in medical imaging. At the same time, lung cancer diagnosis has become a hot research topic, as automated disease detection poses numerous benefits. Although numerous approaches have existed in the literature for lung cancer diagnosis, the design of a novel model to automatically identify lung cancer is a challenging task. In this view, this paper designs an automated machine learning (ML) with data science-enabled lung cancer diagnosis and classification (MLDS-LCDC) using computed tomography (CT) images. The presented model initially employs Gaussian filtering (GF)-based pre-processing technique on the CT images collected from the lung cancer database. Besides, they are fed into the normalized cuts (Ncuts) technique where the nodule in the pre-processed image can be determined. Moreover, the oriented FAST and rotated BRIEF (ORB) technique is applied as a feature extractor. At last, sunflower optimization-based wavelet neural network (SFO-WNN) model is employed for the classification of lung cancer. In order to examine the diagnostic outcome of the MLDS-LCDC model, a set of experiments were carried out and the results are investigated in terms of different aspects. The resultant values demonstrated the effectiveness of the MLDS-LCDC model over the other state-of-The-Art methods with the maximum sensitivity of 97.01%, specificity of 98.64%, and accuracy of 98.11%. 2023 World Scientific Publishing Company.
Vishwa Kiran S.; Kaur I.; Thangaraj K.; Saveetha V.; Kingsy Grace R.; Arulkumar N.
International Journal of Image and Graphics, Vol-23, No. 3
Vishwa Kiran S., Department of AI and ML, BMS Institute of Technology and Management, Karnataka, Bangalore, 560064, India; Kaur I., Department of CSE, Ajay Kumar Garg Engineering College, Uttar Pradesh, Ghaziabad, 201009, India; Thangaraj K., Department of IT, Sona College of Technology, Tamil Nadu, Salem, 636005, India; Saveetha V., Department of IT, Dr. N. G. P Institute of Technology, Tamil Nadu, Coimbatore, 641048, India; Kingsy Grace R., Department of CSE, Sri Ramakrishna Engineering College, Tamil Nadu, Coimbatore, 641022, India; Arulkumar N., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India
EV Service Stations for Future Smart Cities
batteries; Charging Infrastructure; Electric Vehicles; Training; workforce
The market for electric vehicles (EVs) has been growing at a fast pace in recent years. It is expected to continue growing at a much faster pace in the coming decades. The emerging EV technology is increasingly gaining a high demand for continued good transport connections in smart cities. Most of the Smart Cities' charging infrastructure and future growth revolve around its public transport network, especially an EV service station. New technologies, therefore, need to be complemented with new and versatile charging options to cater to different types of charging options available for charging Li-ion Batteries with newer materials and charging capacity. Building an EV service station in the ongoing scenario anticipates smart engineering knowledge to complement innovative charging methods. An EV service station needs hardware, software, and test equipment before charging, during charge, and post-charge states. It is expected to inform the user of available options to choose and select from. This paper investigates the challenges and suggests solutions to meet the EV service station support for EV vehicles in present and future smart cities. It also highlights the demand for a skilled workforce to maintain these service stations, including updating their skills. Examples of a few smart cities in developed as well as developing countries have been quoted. These developments will contribute to the transport infrastructure needed for future smart cities. The paper paves the way for future research in this area. The Institution of Engineering & Technology 2023.
IET Conference Proceedings, Vol-2023, No. 44, pp. 463-466.
Institution of Engineering and Technology
https://doi.org/10.1049/icp.2024.0968 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194252113&doi=10.1049%2ficp.2024.0968&partnerID=40&md5=85c876b67c387c81ffe4df36d4a3bcdd
Vishwakarma S., BC Hydro, Vancouver, Canada; Chaurasia A., School of Commerce Finance Accountancy, Christ University, Ghaziabad, India; Tyagi R., Asian Institute of Technology, Thailand
Pattern of acquisition of theory of mind in pre-schoolers: A cross-sectional study from South India
Collectivistic; Individualistic; Pre-schoolers; Theory of mind
Background: Theory of Mind (ToM) is an important part of children's social cognitive development. The pattern of ToM acquisition depends on many factors including culture, the number of family members, and siblings. This study aimed to examine the pattern of ToM acquisition in Indian culture. Methods: We conducted a cross-sectional study among preschool children (three to six years) (N = 118) from rural and urban backgrounds. ToM development was assessed using the Wellman and Liu Theory of Mind Scale and the Children's Social Understanding Scale (parent report). Results: The order of acquisition of ToM in Indian children was as follows: diverse desire> diverse belief> knowledge access> explicit false belief> content false belief> hidden emotion. The number of siblings positively correlated with the total ToM task score, and the number of adults in the family did not show any positive correlation. Conclusions: Although India is a collectivistic country, the acquisition pattern of ToM in our population was like that of individualistic countries such as the United States. 2023 Elsevier B.V.
Vishwanath R.; Kamath A.G.; Thomas N.; Guddattu V.; Praharaj S.K.
https://doi.org/10.1016/j.ajp.2022.103443 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145658696&doi=10.1016%2fj.ajp.2022.103443&partnerID=40&md5=ac4a08e40478a5e561c3c9f9da1d41f5
Vishwanath R., Department of Psychiatry, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Karnataka, Manipal, India; Kamath A.G., Department of Psychiatry, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Karnataka, Manipal, India; Thomas N., Consultant Clinical Psychologist, Karnataka, Manipal, India, PhD Scholar, Christ University, Karnataka, Bengaluru, India; Guddattu V., Department of Data Science, Prasanna School of Public Health, Manipal Academy of Higher Education, Karnataka, Manipal, India; Praharaj S.K., Department of Psychiatry, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Karnataka, Manipal, India
Kannada translation and validation of Wellman and Liu's theory of mind scale and children's social understanding scale in preschoolers
Children's Social Understanding Scale (CSUS); preschoolers; reliability; translation; validity; Wellman and Liu's Theory of Mind (ToM) scale
Background: Assessing theory of mind (ToM) in children is crucial for understanding social cognition. Wellman and Liu's ToM scale and the Children's Social Understanding Scale (CSUS) have been used to study ToM in children but are not available in the local language. Aim: This study aims to translate both scales into Kannada and validate them in preschool children. Methods: Following the rigorous WHO protocol, we meticulously translated and back-translated Wellman and Liu's ToM and CSUS into Kannada with the help of bilingual experts. Validation involved administering both scales to 118 preschool children aged 3 to 6 years from diverse urban and rural backgrounds in a cross-sectional study, ensuring the scales' applicability across different settings. Results: The Cronbach's alpha values for Wellman and Liu's ToM and the CSUS were 0.769 (95% CI 0.698 to 0.828) and 0.983 (95% CI 0.978 to 0.987), respectively, indicating high internal consistency. The test-retest reliability for Wellman and Liu's ToM scale domains ranged from 0.74 to 0.95, and for the CSUS, it was 0.99, demonstrating good reliability. Pearson's correlation between the domains of two scales ranged from 0.32 to 0.69, suggesting a moderate relationship. Conclusion: Our study findings demonstrate that Kannada translations of Wellman and Liu's ToM and CSUS have good internal consistency, test-retest reliability, and construct validity. These tools will be valuable for understanding social cognition in preschool children. 2024 Indian Journal of Psychiatry.
Vishwanath R.; Kamath A.G.; Thomas N.; Praharaj S.K.
Indian Journal of Psychiatry, Vol-66, No. 12, pp. 1139-1144.
https://doi.org/10.4103/indianjpsychiatry.indianjpsychiatry_524_24 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212178221&doi=10.4103%2findianjpsychiatry.indianjpsychiatry_524_24&partnerID=40&md5=7059ccb39497cbaf5140c72ca8a9c06b
Vishwanath R., Department Of Psychiatry, Kasturba Medical College, Manipal, Manipal Academy Of Higher Education, Karnataka, Manipal, India; Kamath A.G., Department Of Psychiatry, Manipal Hospital, Karnataka, Mangalore, India; Thomas N., Consultant Clinical Psychologist, Karnataka, Mangalore, India, Department Of Psychology, Christ University, Karnataka, Bengaluru, India; Praharaj S.K., Department Of Psychiatry, Kasturba Medical College, Manipal, Manipal Academy Of Higher Education, Karnataka, Manipal, India
Exploring the relationship between esg performance and profitability in Indian power companies
This study aims to assess the relationship and impact of Indian power companies' environment, social, governance (ESG) scores on firm performance. Since 2022, CRISIL Ratings Ltd publishes yearly ESG scores for 225 companies in India. The final 'ESG' score is a composite of individual scores for the three metrics: 'Environment', 'Social', and 'Governance'. This study intends to examine the influence of ESG scores on financial profitability measured by both net profit ratio and return on investment. The existence and degree of association between the variables is measured using correlation and simple linear regression analyses, respectively. The findings suggest that the overall ESG composite score is positively and significantly associated with firm profitability and moderately associated with returns. The 'Governance' metric stands out which has a strong and positive relationship with profitability in particular. These findings advocate that by investing in ESG initiatives, the chances of better financial performance are improved. 2024, IGI Global. All rights reserved.
Viswanath A.; Narayana S.H.; Bellamkonda V.S.; Sunil M.P.
ESG and Ecosystem Services for Sustainability, pp. 171-196.
Viswanath A., Christ University (Deemed), India; Narayana S.H., Christ University (Deemed), India; Bellamkonda V.S., Christ University (Deemed), India; Sunil M.P., Christ University (Deemed), India