Interface between the brain and computer to improve the e-commerce user security experience
Using brain-computer interface (BCI) technology for online shopping offers a state-of-the-art way to address the issue of enhancing user experience by creating more personalized and user-friendly shopping environments. This study explores how brain-computer interfaces (BCIs) can improve e-commerce platforms by better understanding customer preferences, emotional responses, and decision-making tendencies through the collection of real-time neural data. Brain-computer interfaces, or BCIs, use brain activity analysis to provide personalized recommendations, streamline navigation, and improve product displays-all of which contribute to a more enjoyable and rewarding shopping experience. This research examines the effects of BCI-enhanced e-commerce systems on user involvement, contentment, and purchase decisions. An extensive assessment of BCIs' effectiveness in improving the overall shopping experience is conducted through experimental analysis and customer feedback. The results show that adding BCIs to e-commerce systems can significantly boost user engagement and make. 2025, IGI Global Scientific Publishing.
Pathak, Supriya; Priyadharshini, L.; Kulshrestha, Nitin; Sahoo, Ashok Kumar; Gurusamy, M.; Seshanna, Sudarshan V.; Gaffar, Shahul Hameed Abdul
Brain-Computer Interfaces and Applications in Business;pp.249-264
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.4018/979-8-3373-5122-3.ch015 https://www.scopus.com/pages/publications/105013043978?origin=resultslist
Pathak S., Department of Faculty of Management and Commerce, Oriental University, Indore, India; Priyadharshini L., Saveetha School of Law, Saveetha Institute of Medical and Technical Science, India; Kulshrestha N., Department of Commerce, Finance, and Accountancy, Christ University, India; Sahoo A.K., Kalasalingam Academy of Research and Education, India; Gurusamy M., Adarsh Institute of Management and Information Technology, India; Seshanna S.V., CMS Business School, Jain University, India; Gaffar S.H.A., Consolidated Techniques Co. Ltd., Saudi Arabia
Cost effective porous areca nut carbon nanospheres for adsorptive removal of dyes and their binary mixtures
Areca nut; Binary mixture; Methylene blue and methyl orange; Nanoadsorbent; Porous nano spheres; Wastewater
Novel porous nanospheres from areca nuts (ACNPs) were synthesized via one-step pyrolysis without the use of any chemical treatment and the materials were used as adsorbents for the removal of cationic methylene blue (MB) and anionic methyl orange (MO) as well as their binary mixtures. Around, 67 tonnes of areca nut biowaste is generated every year which are then burnt due to their slow rate of decomposition resulting in higher carbon footprints. Biosorbents are generally a preferable alternative for dye adsorption but involve chemical modification for surface enhancement and complex sample treatment. In this work, ACNPs, were investigated for their efficiency in the raw form and were characterized by SEM, EDS, FTIR, XRD, and BET techniques before and after subjecting to the dye adsorption studies. The BET analysis of the adsorbents showed a high specific surface area of 693.8 m2/g when prepared at 1000 C, while the N2 adsorption-desorption plot showed type-IV isotherm, suggesting the microporous nature of the carbon matrix. Batch equilibrium studies showed the removal efficiency of >95% for both the dyes and their binary mixtures under the optimum conditions of 0.15 g/L dosage, 10 ?M concentration and contact time of 70 min. Due to the synergistic effects of the binary dyes, higher removal efficiency of MB compared to MO was observed in the binary mixture. Adsorption results were tested using Langmuir, Freundlich, Temkin, Redlich-Peterson, and Elovich isotherms to assess the best fit of the models. The qm value of MB was found to be 97.37 mg/g, while that of MO was 71.22 mg/g which is higher compared to individual dye components having lower values of 86.12 mg/g and 50.35 mg/g, respectively. Extended Langmuir and Jain and Snoeyink isotherms were used for binary data interpretation. The kinetic results showed good agreement with the Pseudo-second order equation, indicating internal diffusion. The possible mechanism involved electrostatic and ?-? interactions between the dye molecules and ACNPs. This approach is comprehensible and cost effective and can be utilized for dye removal in textile industries. 2023 Elsevier Inc.
Pathania D.; Araballi A.; Fernandes F.; Shivanna J.M.; Sriram G.; Kurkuri M.; Hegde G.; Aminabhavi T.M.
ISSN: 139351; PubMed ID: 36805895; CODEN: ENVRA
https://doi.org/10.1016/j.envres.2023.115521 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148936322&doi=10.1016%2fj.envres.2023.115521&partnerID=40&md5=46416b4d4da2083115be999d06fb4db0
Pathania D., Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, Karnataka, Bangalore, 560029, India; Araballi A., Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, Karnataka, Bangalore, 560029, India; Fernandes F., Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, Karnataka, Bangalore, 560029, India; Shivanna J.M., Department of Chemistry, AMC Engineering College, Bannerghatta Road, Bengaluru, 560083, India; Sriram G., 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, Bengaluru, 562112, India; Hegde G., Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, Karnataka, Bangalore, 560029, India, Department of Chemistry, CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, Karnataka, Bangalore, 560029, India; Aminabhavi T.M., Center for Energy and Environment, School of Advanced Sciences, KLE Technological University, Hubballi, 580 031, India, Department of Biotechnology, Engineering and Food Technology, Chandigarh University, Punjab, Mohali, 140413, India
Garlic peel based mesoporous carbon nanospheres for an effective removal of malachite green dye from aqueous solutions: Detailed isotherms and kinetics
Adsorption studies; Biosorbents; Biowaste; Dye removal; Garlic peel; Malachite green; Nanoparticles
Biowaste based nanoadsorbents have gained much attention in the recent times for wastewater decolourization owing to their low cost, high surface area and high adsorption capacities. In the present research, garlic peel based nanoparticles (GCNP) were synthesized at different temperatures by a one step pyrolytic green approach for the effective removal of cationic dye, malachite green from the aqueous medium. The surface properties of Garlic nanoparticles were elucidated by N2 adsorption- desorption and all the GCNP samples were found to exhibit Type IV(a) isotherm indicating the presence of mesopores in carbon matrix. Using BET calculations, highest surface area (380 m2/g) was obtained for GCNP synthesized at 1000 ?C. Characterization of nanoparticles was done by XRD, EDAX, SEM and FTIR studies before and after the dye treatment. Adsorption studies conducted using different parameters like contact time, concentration and pH and dosage of adsorbent showed removal efficiency above 90% for the contact time of 70 min. Best adsorption experimental results were obtained for GCNP synthesized at 1000 C ascribable to its high surface area, higher total pore volume (0.26 cm2/g) and higher carbon content. Four adsorption isotherm models were used to validate batch equillibrium studies and the results showed data in good agreement with Langmuir and Freundlich isotherms with maximum Langmuir adsorbtion capactiy to be 373.7 mg/g. Kinetic modelling of the data showed best fit with the Pseudo second order model with rate constant value of 48.726 g mg?1 min?1. Regenerative studies were conducted conducted upto 6 cycles. Also the GC nanoparticles were tested for their compatibility in membrane form wherein, removal efficiency results were obtained for GCNP anchored in polyvinyl difluoride (PVDF) and polysulfone (PSF) membrane matrix for dye adsorption. 2022 Elsevier B.V.
Pathania D.; Bhat V.S.; Mannekote Shivanna J.; Sriram G.; Kurkuri M.; Hegde G.
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, Vol-276
https://doi.org/10.1016/j.saa.2022.121197 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127467856&doi=10.1016%2fj.saa.2022.121197&partnerID=40&md5=ab2aeaed399511b9024c11c239477f85
Pathania D., Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, S.G. Palya, Karnataka, Bangalore, 560029, India; Bhat V.S., Department of Material Sciences, Mangalore University, Mangalore, Mangalagangothri, 574199, India; Mannekote Shivanna J., Department of Chemistry, AMC Engineering College, Bannerghatta Road, Bengaluru, 560083, India; Sriram G., Centre for Research in Functional Materials (CRFM), JAIN University, Jain Global Campus, Bengaluru, 562 112, India; Kurkuri M., Centre for Research in Functional Materials (CRFM), JAIN University, Jain Global Campus, Bengaluru, 562 112, India; Hegde G., Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, S.G. Palya, Karnataka, Bangalore, 560029, India, Department of Chemistry, CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, S.G. Palya, Karnataka, Bengaluru, 560029, India
Diagnose Diabetic Mellitus Illness Based on IoT Smart Architecture
Obtaining a quick remote diagnosis of heart disease has proven problematic in recent days. To overcome such issues in e-Healthcare systems, Internet of Things (IoT) applications have been deployed using cloud computing (CC) approaches. There are still a number of disadvantages to using CC, including latency, bandwidth, energy usage, and security and privacy concerns. Fog computing (FC), a CC development, may be able to overcome these obstacles. DiaFog enabling remote users for real-time diagnosis of diabetic mellitus disease (DMD) has been proposed in this study, which is based on the combined ideas of IoT, cloud, and fog computing, as well as an ensemble deep learning (EDL) technique. The proposed system is trained with EDL approaches on the integrated dataset of two diabetes mellitus disease datasets (DMDDs), namely, Pima Indians Diabetes Dataset (PIDD) and Hospital Frankfurt Germany Diabetes Dataset (HFGDD), obtained from the UCI-ML and Kaggle repository, respectively, and the integrated dataset of these two. The suggested system has been used to demonstrate accuracy, precision, recall, F-measure, latency, arbitration time, jitter, processing time, throughput, energy consumption, bandwidth utilization, network utilization, scalability, and more. In the remote instantaneous diagnosis of diabetic patients, the integration of IoT-fog-cloud is useful. The results of the trials show the value of employing FC principles and their applicability for speedy diabetic patient remote diagnosis. PACS-key is describing text of that key PACS-key describing text of that key. 2022 Abhilash Pati et al.
Pati A.; Parhi M.; Pattanayak B.K.; Singh D.; Samanta D.; Banerjee A.; Biring S.; Dalapati G.K.
Wireless Communications and Mobile Computing, Vol-2022
Pati A., Siksha 'o' Anusandhan University, Odisha, Bhubaneswar, India; Parhi M., Siksha 'o' Anusandhan University, Odisha, Bhubaneswar, India; Pattanayak B.K., Siksha 'o' Anusandhan University, Odisha, Bhubaneswar, India; Singh D., Siksha 'o' Anusandhan University, Odisha, Bhubaneswar, India; Samanta D., Department of Computer Science, CHRIST University, Bangalore, India; Banerjee A., Physics Department, Bidhan Chandra College, Asansol, 713 303, India, Organic Electronics Research Center, Ming Chi University of Technology, New Taipei City, 24301, Taiwan; Biring S., Organic Electronics Research Center, Ming Chi University of Technology, New Taipei City, 24301, Taiwan, Department of Electronic Engineering, Ming Chi University of Technology, New Taipei City, 24301, Taiwan; Dalapati G.K., Organic Electronics Research Center, Ming Chi University of Technology, New Taipei City, 24301, Taiwan, Sunkonnect, 1 Cleantech Loop, Singapore, 637141, Singapore
Effect of samarium doping on structural properties and electronic structure of Bi0.5Na0.5TiO3ceramic with antimicrobial applications
Antimicrobial properties; Electronic and local structure; Microstructure; Structure
The research work reports a systematic examination of structure, microstructure, electronic and local structure, optical and antimicrobial properties of Bi0.5Na0.5TiO3 (BNT) and Bi0.45Sm0.05Na0.5TiO3 (BSNT) ceramics manufactured by the solid-state route. The influence of a small amount of samarium (Sm) doping at the A-site of BNT matrix is examined using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, field emission-scanning electron microscopy (FESEM), energy dispersive X-ray spectroscopy (EDS), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), X-ray absorption near edge spectroscopy (XANES) and extended X-ray absorption fine structure spectroscopy (EXAFS), UVvis diffused reflectance spectroscopy (DRS), and antimicrobial analyses. XRD reveals single-phase rhombohedral structures with R3c space group. FTIR provides evidence for perovskite structures. Raman spectra illustrate three prominent vibrations, like Bi - O/Na - O, Ti - O vibrations of TiO6, and oxygen ion vibrations of the TiO6 octahedron of both samples. FESEM reveals better grain developments, and elemental confirmations are evident from EDS. The topographical and morphological studies, such as RMS and average roughness, skewness, and kurtosis, are conducted by AFM. XPS reveals dual oxidation states of Ti and Sm, and oxygen vacancies (OVs). A detailed analysis of the electronic structure is performed by examining the Bi L3-edge and Ti K-edge XANES spectra of BNT and BSNT, along with those of the model compounds. The Fourier transform of EXAFS analysis is conducted to probe the local structure, and extracted parameters, like coordination number (N), bond distance (R(), and Debye-Waller factor (?2), are analyzed. UVvis studies reveal a minute reduction in the band gap in BSNT. Impedance study shows the negative temperature coefficient of resistance (NTCR) responses. The antibacterial activities are examined by determining the minimum inhibitory concentration (MIC) and zone of inhibition (ZOI) caused by the materials, along with a control antibiotic, against a variety of bacterial strains. 2025 Elsevier Ltd and Techna Group S.r.l. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Pati, Dinesh Kumar; Mahapatra, Shreyash; Mahapatra, Mitrabinda; Chakroborty, Subhendu; Malviya, Jitendra; Das, Piyush R.; Dwivedi, Rajeev; Parida, B.N.; Urkude, Rajashri R.; Padhee, R.
Ceramics International;Volume;51;Issue;30;pp.62395-62414
https://doi.org/10.1016/j.ceramint.2025.10.369 https://www.scopus.com/pages/publications/105024759177?origin=resultslist
Pati D.K., School of Physics, Sambalpur University, Jyoti Vihar, Odisha, Burla, 768019, India, Newton Higher Secondary School of Science, Debaipali, Odisha, Sambalpur, 768200, India; Mahapatra S., Newton Higher Secondary School of Science, Debaipali, Odisha, Sambalpur, 768200, India; Mahapatra M., School of Physics, Sambalpur University, Jyoti Vihar, Odisha, Burla, 768019, India; Chakroborty S., Department of Chemistry, School of Basic Sciences, Chandigarh University Uttar Pradesh, Uttar Pradesh, Unnao, 209859, India; Malviya J., Department of Microbiology, Barkatullah University, MP, Bhopal, 462026, India; Das P.R., Department of Physics, CUPGS, BPUT, Chhend, Odisha, Rourkela, 769015, India; Dwivedi R., Department of Physics, Bennett University, U.P., Greater Noida, 201310, India; Parida B.N., Department of Physics, Central Institute of Technology Kokrajhar, Deemed to be University, BTC, Assam, 783370, India; Urkude R.R., Beamline Development and Application Section, BARC, Trombay, Mumbai, 400085, India; Padhee R., School of Physics, Sambalpur University, Jyoti Vihar, Odisha, Burla, 768019, India
Comparative analysis and suggestion of architectures for reduction of road accidents
Architectures; Road Accidents; Sensors; Technology; Vehicles
As Road Accidents are increasing all over the world, it is very important to save peoples lives. With the advancement in technology we can make use of various real time sensors and technology to save peoples lives. This paper focuses on comparing various architectures which consists of various real time sensors like Eye blink sensor, Alcohol sensor, Speed sensor, load sensor, tilt and turning sensor and various technologies like GPS, GSM. After comparison paper suggests which architecture should be used in the vehicle based on certain attributes. For E.g. If the car always travels outside the city then this paper suggests the architecture which has Eye blink sensor, Speed Sensor GPS and GSM. IAEME Publication.
International Journal of Civil Engineering and Technology, Vol-9, No. 3, pp. 945-954.
Patil A., Department of Computer Science, Christ University, Bangalore, India; Das D., Department of Computer Science, Christ University, Bangalore, India
Big data-Industry 4.0 readiness factors for sustainable supply chain management: Towards circularity
Big data; Circular Economy; Digitalization; Industry 4.0; Sustainable Supply Chain
Big data-Industry 4.0 interaction is expected to revolutionize the existing supply chains in recent years. While increased operational efficiency and enhanced decision-making are the primary advantages studied widely, the sustainable aspects of digital supply chain in the circular economy era have received limited attention. The previous literature rarely explores the industry readiness for a digital supply chain. Thus, the present study objectives to explore Big data-Industry 4.0 readiness factors for sustainable supply chain management. A detailed literature analysis was performed to identify a total of seventeen readiness factors for sustainable supply chain management. A team of six experts were consulted to perform the pairwise comparison for the identified potential readiness factors. This study adopts a fuzzy best-worst method to prioritize the readiness factors according to their degree of influence. The results from the study reflect that readiness towards information system infrastructure, Internet stability for developing I4.0 infrastructure, and circular process and awareness are the most significant readiness factors. The potential recommendation of this study includes the increased attention from sustainable supply chain stakeholders on developing infrastructure, including knowledge building exercise and training process focused on circular economy process. The findings from the study will assist sustainable supply chain stakeholders to frame strategies and action plans during the digitalization of supply chains. 2023 Elsevier Ltd
Patil A.; Dwivedi A.; Abdul Moktadir M.; Lakshay
Computers and Industrial Engineering, Vol-178
https://doi.org/10.1016/j.cie.2023.109109 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149638220&doi=10.1016%2fj.cie.2023.109109&partnerID=40&md5=655fa597973507a2da5d5f29d541d9fe
Patil A., Christ University, Bengaluru, India; Dwivedi A., Jindal Global Business School, O.P. Jindal Global University, Sonipat, India; Abdul Moktadir M., Institute of Leather Engineering and Technology, University of Dhaka, Dhaka, 1209, Bangladesh; Lakshay, Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, India
Effects of Macro Economic Indicators on Foreign Portfolio Investments
Foreign Portfolio Investment; Gross Domestic Product; Monetary Policy; National Stock Exchange Volume; the VECM (Vector Error Correction) Model
In this study, both institutional and retail investors were observed making exits and entries based on macroeconomic data, utilizing measurable indicators such as GDP, inflation, bank rates, foreign exchange rates, trade volume on the national stock exchange, and portfolio investments. Employing a Vector Error Correction Model (VECM) in an econometric analysis, the study found a significant association between macroeconomic indicators and portfolio investments in India. Investors followed a discernible pattern of entering and exiting markets, with economic growth fostering greater investments. Notably, GDP, NSE Volume, and bank rates were identified as variables impacting foreign portfolio investments. In the long run, GDP positively affected foreign portfolio investments, while inflation and foreign exchange rates exhibited a detrimental influence, leading to decreased portfolio investments. Foreign Institutional Investors, prioritizing profits over business operations, focused on market sentiments, directing investments towards economies with potential performance and resulting in a higher volume of capital inflow. Overall, the study concludes that a robust economic condition attracts superior foreign portfolio investments. 2024 IEEE.
Patil A.; Lakshmi R.B.; Niranjan L.R.; Vas J.
Proceedings of 9th International Conference on Science, Technology, Engineering and Mathematics: The Role of Emerging Technologies in Digital Transformation, ICONSTEM 2024
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICONSTEM60960.2024.10568614 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198841367&doi=10.1109%2fICONSTEM60960.2024.10568614&partnerID=40&md5=a4db7b165063fbdba1ba75ad2609c45e
Patil A., School of Business & Management, Christ University, Bangalore, India; Lakshmi R.B., School of Business & Management, Christ University, Bangalore, India; Niranjan L.R., School of Business & Management, Christ University, Bangalore, India; Vas J., School of Business & Management, Christ University, Bangalore, India
An in-depth investigation into financial literacy levels in Indian households
In a complex financial world, lack of awareness complicates money management and savings. Emphasizing financial literacy is vital for informed decision-making. This study explores global financial illiteracy, advocating international initiatives. In India, it assesses disparities and government activities and reviews tax-saving and mobile banking. Gaps include limited studies on Indian households, necessitating gender-specific analyses and research on education's impact. The methodology outlines justification, operational definitions, and data collection techniques. With ANOVA and descriptive statistics on 285 respondents, the study reveals demographic analysis, indicating higher financial literacy with age and a gender gap. Education. positively correlates with financial literacy. Recommendations include interventions like financial seminars, collaboration with regulators, and destigmatizing money talks at home to enhance financial literacy and bridge gaps. 2024 by IGI Global. All rights reserved.
Patil A.; Niranjan L.R.; Patavardhan R.; Jain V.
Contemporary Research and Practices for Promoting Financial Literacy and Sustainability, pp. 113-146.
Patil A., Christ University, India; Niranjan L.R., Christ University, India; Patavardhan R., Christ University, India; Jain V., Christ University, India
Role of ICT in economic empowerment of women by being an effective facilitator for women entrepreneurship
Information and communication technology (ICT) is steadily gaining dominance over other channels as a standalone medium for gaining and sharing knowledge, hybrid working environment, network strengthening and funding, business collaborations, new venture set-up, marketing and branding. ICT being most effectively featured with accessibility and omnipresence has been capable of empowering a lot of developing and talent-rich areas, and women empowerment is one among them. This chapter makes an attempt to bring out the efficient role played by ICT in enhancing the lifestyle of women. It proposes to provide a detailed description of how ICT has empowered women, and entrepreneurs, to set up and develop their business ventures giving them access to required resources and making them more competent through information and wider access to the market. This chapter presents its findings based on a systematic review of different case analyses by using secondary data. The findings will be also supported by the evidence and information gathered from credible reports, articles, and publications. 2023, IGI Global.
Patil A.; Prathibha Raj M.S.; Thomas R.; Sarkar B.
ICT as a Driver of Women's Social and Economic Empowerment, pp. 77-101.
Patil A., CHRIST University (Deemed), India; Prathibha Raj M.S., CHRIST University (Deemed), India; Thomas R., CHRIST University (Deemed), India; Sarkar B., CHRIST University (Deemed), India
An integrated framework for digitalization of humanitarian supply chains in post COVID-19 era
Digitalization; Humanitarian supply chain; Neutrosophic DEMATEL; Post COVID-19; Principal component analysis
Digital Supply Chains (DSCs) are transforming industries across various domains. Digitalization can improve coordination, increase data collection and retention capacities, enhance funding mechanisms, and improve operational performance and resource utilization. However, DSC adoption is constrained by lack of funding, operational complexities, infrastructure issues, etc. Thus, the need emerges to explore the digitalization of the Humanitarian Supply Chain (HSC) and provide solutions that can ease the adoption of DSC. In this study, a framework is created to facilitate the digitalization process of HSC in post COVID-19 era. Nineteen related drivers are identified with the potential to digitalize the HSC. The drivers are identified from the previous literature and finalized with the assistance of HSC stakeholders. A Principal Component Analysis is carried out to discover the most pertinent drivers from the identified list of drivers. A Kappa analysis is adopted to perfect the priority map of the digitalization drivers. Further, the neutrosophic DEMATEL methodology is adopted to prioritize the potential drivers and find their dependency on each other. The results from the study indicate that the most influential drivers fall under the operational and technological categories. However, the social drivers have the potential to play a significant contribution in an effort to HSC digitalization. In addition, the study presents strategies for enhancing funds collection and data management using emerging technologies. These strategies can assist HSC decision-makers in formulating relevant policies and strategic interventions. 2023 Elsevier Ltd
Patil A.; Shardeo V.; Dwivedi A.; Paul S.K.
International Journal of Disaster Risk Reduction, Vol-87
https://doi.org/10.1016/j.ijdrr.2023.103574 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147880035&doi=10.1016%2fj.ijdrr.2023.103574&partnerID=40&md5=db7ce3a8269f7b407e7489253b4f2bdf
Patil A., Christ University, Bengaluru, India; Shardeo V., Lal Bahadur Shastri Institute of Management, New Delhi, India; Dwivedi A., Jindal Global Business School, O.P. Jindal Global University, Sonipat, India; Paul S.K., UTS Business School, University of Technology Sydney, Sydney, Australia
Digital twins' readiness anditsimpacts on supply chaintransparency andsustainable performance
Digital twins technology; Supply chain; Sustainable performance; Transparency
Purpose: Production systems occupy geographically dispersed organizations with limited visibility and transparency. Such limitations create operational inefficiencies across the Supply Chain (SC). Recently, researchers have started exploring applications of Digital Twins Technology (DTT) to improve SC operations. In this context, there is a need to provide comprehensive theoretical knowledge and frameworks to help stakeholders understand the adoption of DTT. This study aims to fulfill the research gap by empirically investigating DTT readiness to enable transparency in SC. Design/methodology/approach: A comprehensive literature survey was conducted to develop a theoretical model related to Supply Chain Transparency (SCT) and DTT readiness. Then, a questionnaire was developed based on the proposed theoretical model, and data was collected from Indian manufacturers. The data was analyzed using Confirmatory Factor Analysis (CFA) and Structural EquationModelling (SEM) to confirm the proposed relationships. Findings: The findings from the study confirmed a positive relationship between DTT implementation and SCT. This study reported that data readiness, perceived values and benefits of DTT, and organizational readiness and leadership support influence DTT readiness and further lead to SCT. Originality/value: This study contributes to the literature and knowledge by uniquely mapping and validating various interactions between DTT readiness and sustainable SC performance. 2024, Emerald Publishing Limited.
Patil A.; Srivastava S.; Paul S.K.; Dwivedi A.
Industrial Management and Data Systems, Vol-124, No. 8, pp. 2532-2566.
https://doi.org/10.1108/IMDS-10-2023-0767 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196487226&doi=10.1108%2fIMDS-10-2023-0767&partnerID=40&md5=e89e7723e8190d7ade4cd2d49a7aa37c
Patil A., International Management Institute, New Delhi, India; Srivastava S., Christ University, Bangalore, India; Paul S.K., UTS Business School, University of Technology Sydney, Sydney, Australia; Dwivedi A., Jindal Global Business School, Jindal Global University, OP, Sonipat, India
A Study of Segmentation Techniques to Detect Leukaemia in Microscopic Blood Smear Images
Active contour; Acute lymphoblastic Leukemia; Artificial neural network; Fuzzy c-mean; Image segmentation; k-means; Region growing; Thresholding; watershed
In medical image processing, the segmentation of the image is considered to be a vital stage and is effectively used to extract the region of interest. Automated diagnosis of leukaemia is highly associated with the accurate segmentation of the cell nucleus. The purpose of this paper is to review and analyze literature related to some of the major segmentation techniques used in the field of Acute lymphoblastic leukaemia (ALL) detection. This paper presents an overview of segmentation methods along with the experimental results of six implemented methods and highlights some of the advantages and disadvantages of implemented segmentation techniques. 2020 IEEE.
Proceedings of the 2020 IEEE International Conference on Communication, Computing and Industry 4.0, C2I4 2020
Patil A.P., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India, Department of Computer Application, CMR Institute of Technology, Bengaluru, India
Acute Leukemia Subtype Recognition in Blood Smear Images with Machine Learning
Acute Leukemia; cell analysis; Image processing; Leukemia Classification; Segmentation
Acute leukemia is a swiftly progressing blood cancer affecting white blood cells which poses a significant threat to the immune system and often leads to fatal outcomes if not detected and treated promptly. The current manual diagnostic method, being time-consuming and prone to errors, necessitates an urgent shift toward a comprehensive automated system. This paper presents an innovative approach to automatically identify acute leukemia cells and their subtypes by analyzing microscopic blood smear images. The proposed methodology involves the segmentation of clustered lymphocytes, isolation of nuclei, and extraction of diverse features from each nucleus. A random forest classifier is then trained to categorize nuclei into healthy or cancerous, with further precision in classifying cancerous nuclei into specific subtypes. The method achieves an impressive 97% accuracy across all evaluations, holding profound implications for pathologists and medical practitioners in their decision-making processes. 2024, J.J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology. All rights reserved.
International Journal of Electrical and Computer Engineering Systems, Vol-15, No. 7, pp. 563-570.
J.J. Strossmayer University of Osijek , Faculty of Electrical Engineering, Computer Science and Information Technology
https://doi.org/10.32985/ijeces.15.7.2 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199139463&doi=10.32985%2fijeces.15.7.2&partnerID=40&md5=9bd641d0c97f8c41adb4912167c1d886
Patil A.P., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Hiremath M., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India
Segment Anything Model (SAM) to Segment lymphocyte from Blood Smear Images
Deep learning; Lymphocyte; Segment Anything Model; Segmentation; white blood cells
Automated lymphocyte segmentation from smear images plays an important role in disease diagnosis and monitoring, aiding in the assessment of immune system function and pathology detection. This study proposes an approach for lymphocyte segmentation utilizing Segment Anything Model (SAM) which is a deep learning model. Our method leverages a pre trained SAM architecture and fine-tunes it on a custom dataset comprising smear images containing lymphocytes. The pretrained model's ability of versatile segmentation combined with fine-tuning on the specific dataset enhances its performance in accurately identifying lymphocyte boundaries. We evaluate the proposed approach on a diverse set of smear images, demonstrating its effectiveness in segmenting lymphocytes with impressive IOU score and Dice Score. SAM deep learning model, fine-tuned on custom datasets, holds promise for robust and efficient lymphocyte segmentation from blood smear images. 2024 IEEE.
2024 IEEE 3rd World Conference on Applied Intelligence and Computing, AIC 2024, pp. 1080-1084.
https://doi.org/10.1109/AIC61668.2024.10730867 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210268951&doi=10.1109%2fAIC61668.2024.10730867&partnerID=40&md5=36cc6adea1bbf1eee90d6f1b7b2f1179
Patil A.P., Christ (Deemed to Be University), Department of Computer Science, India, Cmr Institute of Technology, Department of Computer Application, Bengaluru, India; Hiremath M., Christ (Deemed to Be University), Department of Computer Science, Bengaluru, India
Machine Learning Model to Detect Chronic Leukemia in Microscopic Blood Smear Images
Chronic lymphocytic Leukemia; Chronic Myeloid Leukemia; image processing; Machine Learning; Random Forest; Watershed Segmentation
Chronic leukemia is a slow-progressing form of disease, If not diagnosed on time can progress and increase the risk of life-threatening complications. It is essential to develop a fully automated system to recognize and categorize type of leukemia for proper evaluation and treatment. This paper aims to provide a machine learning model to identify and classify chronic lymphocytic leukemia, chronic myeloid Leukemia and healthy cells. Digital microscopic blood smear images were automatically cropped into single nucleus and segmented using watershed algorithm. Grey level co-occurrence matrix (GLCM) and geometrical features were extracted from the segmented nucleus images and random forest algorithm is used to classify chronic leukemia and healthy cells. This prognosis aids pathologists and physicians in identifying leukemic patients early and selecting the most effective course of action. 2023 IEEE.
Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications
Patil A.P., CHRIST (Deemed to Be University), Department of Computer Science, Bengaluru, India; Hiremath M., CMR Institute of Technology, Department of Computer Application, Bengaluru, India
A Study of Preprocessing Techniques on Digital Microscopic Blood Smear Images to Detect Leukemia
Bilateral; Gaussian; Leukemia; Median; Noise reduction; Wiener
Digital microscopic blood smear images can get distorted due to the noise as a result of excessive staining during slide preparation or external factors during the acquisition of images. Noise in the image can affect the output of further steps in image processing and can have an impact on the accuracy of results. Hence, it is always better to denoise the image before feeding it to the automatic diagnostic system. There are many noise reduction filters available; the selection of the best filter is also very important. This paper presents a comparative study of some common spatial filters like wiener filter, bilateral filter, Gaussian filter, median filter and mean filter which are efficient in noise reduction, along with their summary and experimental results. Performing comparative analysis of result based on PSNR, SNR and MSE values, it can be determined that median filter is most suitable method for denoising digital blood smear images. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Networks and Systems, Vol-462, pp. 275-282.
Springer Science and Business Media Deutschland GmbH
Patil A.P., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India, Department of Computer Application, CMR Institute of Technology, Bengaluru, India; Hiremath M., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Kavipriya K., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India
A Unified Approach to Predict and Understand Acute Myeloid Leukemia Diagnosis
Acute myeloid leukemia; Classification; Explainable AI; LIME; SHAP feature importance
Acute myeloid leukemia (AML) is a rapidly progressing disease that affects myeloid cells in blood and bone marrow. These abnormal cancerous cells called blast cells are non-functional cells that increase rapidly in bone marrow and are released into blood stream which crowd out the healthy functional cells leading to weak immune system. This life-threatening disease needs to be diagnosed at early stage and hence requires fully automated system for early detection of leukemia to aid pathologists and doctors. Most of the automated machine learning and AI models are not transparent and require techniques to explain model prediction. This paper presents methods to classify blood microscopic images into healthy or acute myeloid leukemia. Among all the methods implemented, Gradient Boosting outperforms with an accuracy of 96.67%. This paper also focuses on explainable AI to interpret model prediction and feature importance which further helps in understanding decision-making process of classification model and optimize it. 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Electrical Engineering, Vol-1098, pp. 233-242.
Patil A.P., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Hiremath M., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Pawar V., Department of Computer Applications, CMR Institute of Technology, Bengaluru, India
Quantitative assessment of blockchain applications for Industry 4.0 in manufacturing sector
Blockchain; Industry 4.0; Manufacturing; Technology
Blockchain is one of the emerging digital technologies that will play a role in the breakthroughs of the fourth industrial revolution. The use of blockchain technology has the potential to greatly benefit businesses of all sizes by increasing their data's integrity, privacy, and openness. The term Industry 4.0? refers to the amalgamation of recent advances in manufacturing technology that have helped businesses cut production times significantly. The industrial and supply chain industries can benefit from these technological advancements in a number of ways. Increased efficiency in production and a more stable supply chain are just two of the many benefits that blockchain promises to bring to the manufacturing industry. The study focuses on Blockchain's huge potential in the context of Industry 4.0. Understanding the role of Blockchain technology in Industry 4.0 is examined, along with its various drivers, enablers, and associated capabilities. The several sub-domains of Industry 4.0 that can benefit from the implementation of Blockchain technology are also covered. The present research is primary and exploratory in nature. The sample size of the study is 256. The responses obtained from workers working in manufacturing sector in Delhi/NCR. The responses from workers obtained through structured questionnaire. The several sub-domains of Industry 4.0 found that can benefit from the implementation of Blockchain technology. At last, the existing study found the most important uses of Blockchain technology in the fourth industrial revolution. 2023
Patil B.S.; .K. Sharma M.; Soubhari T.; Ashok J.; Pandey V.; Joshi G.
https://doi.org/10.1016/j.matpr.2023.04.366 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153929728&doi=10.1016%2fj.matpr.2023.04.366&partnerID=40&md5=e958c626505b1a841877c7278707fae5
Patil B.S., Dayananda Sagar Business School, Karnataka, Bengaluru, India; .K. Sharma M., Department of Mathematics, Chaudhary Charan Singh University, U.P, Meerut, India; Soubhari T., N.S.S. College, Manjeri, University of Calicut, Kerala, India; Ashok J., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Pandey V., Department of Management, Amity University, Bihar, Patna, India; Joshi G., Lal Bahadur Shastri Institute of Management, New Delhi, India
A Comparison of Similarity Measures in an Online Book Recommendation System
Books; Collaborative filtering; Machine learning; Recommendation system; Similarity; User
To assist users in identifying the right book, recommendation systems are crucial to e-commerce websites. Methodologies that recommend data can lead to the collection of irrelevant data, thus losing the ability to attract users and complete their work in a swift and consistent manner. Using the proposed method, information can be used to offer useful information to the user to help enable him or her to make informed decisions. Training, feedback, management, reporting, and configuration are all included. Our research evaluated user-based collaborative filtering (UBCF) and estimated the performance of similarity measures (distance) in recommending books, music, and goods. Several years have passed since recommendation systems were first developed. Many people struggle with figuring out what book to read next. When students do not have a solid understanding of a topic, it can be difficult determining which textbook or reference they should read. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes on Data Engineering and Communications Technologies, Vol-131, pp. 341-349.
Patil D., Christ University, Bengaluru, India; Preethi N., Christ University, Bengaluru, India