Promoting Net-Zero Economy for Sustainable Development: Practice-Based View
Carbon neutrality; Environmental consideration; Net zero; Resource; Responsible business conduct; Sustainability
The present research investigates the utilization of various resources, including tangible assets, human expertise, and intangible assets, in a cohesive set of established procedures, which impact the development and implementation of net-zero practices. It also explores the effect on the environmental performance of SME enterprises operating in business markets. Additionally, the study explores whether digitalization plays a moderating role in this relationship. The samples of 291 were used in the study. Data were analyzed using partial least square structural equation modeling. For a sustainable net-zero economy (SNZE), it is essential for managers to acknowledge the importance of resource and capabilities management. While the management of tangible assets and human skills is vital, greater emphasis should be placed on intangible resources like organizational culture and learning. Furthermore, the capacity of small-sized enterprises (SMEs) to process and implement knowledge could prove to be instrumental in accomplishing net-zero targets. Consequently, managers should leverage Industry-4.0-based technological solutions to enhance resource and capabilities management effectively. This research pioneers an exploration into the influence of human capital and various assets (tangible and intangible), on the development and implementation of a SNZE in organizations, underpinned by empirical data. The study broadens the understanding of the practice-based view (PBV) framework in realizing SNZE, particularly within SME B2B enterprises. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Sharma A.; Chaudhary M.; Kumar K.; Daga S.
CSR, Sustainability, Ethics and Governance, Vol-Part F2880, pp. 101-116.
Sharma A., Christ University, Bengaluru, India; Chaudhary M., College of Business and Law, Royal University of Women, Riffa, Bahrain; Kumar K., Christ University, Bengaluru, India; Daga S., PGDAV College, University of Delhi, Delhi, India
Face Detection-Based Border Security System Using Haar-Cascade and LBPH Algorithm
Border security; Border surveillance; Criminal identification; Face detection; Face recognition; Haar-Cascade classifier; LBPH
Border security is a process which measures the border management ideas by a country or set of countries to wage against unspecific and unauthorized travel or trade across the country borders, to bound non-legal deport, various crimes combat, and foreclose dangerous criminals from entering in the country. A system will help in keeping a check on those personnels who forge with the legal document with an intension to cross the border. This article discusses about border security of whole Indian context, and there are various such systems which have been built since 2010 as wireless sensor network system named Panchendriya. Remote and instruction manual switch mode arm system using ultrasonic sensor for security of border. This article we have made use of Haar-Cascadian along with LBPH algorithm with their functioning. The result and discussion section we compare most recent face recognition techniques that have been used in the last ten years. The proposed prototype is discussed and shown through simulation model, it provide better result compare to existing model. The proposed Haar-Cascade and LBPH algorithm provide 10% better performance. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Networks and Systems, Vol-551, pp. 25-38.
Springer Science and Business Media Deutschland GmbH
Sharma A., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Kengeri Campus, Bangalore, India; Jayapandian N., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Kengeri Campus, Bangalore, India
Inventory model for deteriorating items with ramp type demand under permissible delay in payment
Deterioration; Nonlinear demand function; Permissible delay; Shortage
Permissible delay in payment is a common method of payment often used by the suppliers and it generally leads to higher sales and ultimately higher revenue. This method is significant in the case of deteriorating products. In this paper, an inventory model for the deteriorating items with price and time-dependent ramp type demand is presented with shortages allowed and partially backlogged. The solution procedure is illustrated by numerical examples. The concavity of the profit function with respect to the decision variable is discussed analytically. Numerical analysis shows that the profit per unit time increases with the delay payment facility. Copyright 2021 Inderscience Enterprises Ltd.
International Journal of Procurement Management, Vol-14, No. 5, pp. 578-595.
https://doi.org/10.1504/IJPM.2021.117292 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114366109&doi=10.1504%2fIJPM.2021.117292&partnerID=40&md5=945419c653100c6cd7260bb01e928e7c
Sharma A., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India; Kaushik J., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India, Department of Data Science, CHRIST (Deemed to be University), 30 Valor Court, Dasve Cir, Lavasa, India
Subsume Pediatric Headaches in Psychiatric Disorders? Critiques on Delphic Nosology, Diagnostic Conundrums, and Variability in the Interventions
Children and adolescents; Pediatric headaches; Primary headaches; Tension-type headache
Purpose of Review: Tension-type headache (TTH) continues to be the most prevalent type of headache across all age groups worldwide, and the global burden of migraine and TTH together account for 7% of all-cause years lived with disability (YLDs). TTH has been shown to have a prevalence of up to 80% in several studies and presents a wide range and high variability in clinical settings. The aim of this review is to identify gaps in diagnostics, nosology, and variability in the treatment of children and adolescents who present with headaches without an identifiable etiology. Recent Findings: Migraine and TTH have been debated to have more similarities than distinctions, increasing chances of misdiagnosis and leading to significant cases diagnosed as probable TTH or probable migraine. The lack of specificity and sensitivity for TTH classification often leads to the diagnosis being made by negating associated migraine symptoms. Although pathology is not well understood, some studies have suggested a neurological basis for TTH, in need of further validation. Some research indicates that nitric oxide signaling plays an integral part in the pain mechanisms related to TTH. Analgesics and non-steroidal anti-inflammatories are usually the first lines of treatment for children with recurring headaches, and additional treatment options include medication and behavioral therapies. Summary: With high prevalence and socioeconomic burden among children and adolescents, its essential to further study Tension-type headaches and secondary headaches without known cause and potential interventions. Treatment studies involving randomized controlled trials are also needed to test the efficacy of various treatments further. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Sharma A.; Khurana P.; Venkatraman A.; Gupta M.
Current Pain and Headache Reports, Vol-28, No. 7, pp. 651-662.
ISSN: 15313433; PubMed ID: 38367199; CODEN: CPHRG
Sharma A., Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, United States; Khurana P., Department of Psychology, Christ University, NCR, Delhi, India; Venkatraman A., Department of Pediatric Neurology, Geisinger Health System, Danville, PA, United States; Gupta M., Southwood Psychiatric Hospital, Pittsburgh, PA, United States
Consolidation of Cloud Computing in Smart and Sustainable Environment
Cloud Applications; Cloud Architecture; Cloud storage; Information processing; Sensory model; Sustainable computing
Cloud computing has revolutionized IoT device data collection, administration, and analysis by offering a scalable and sustainable solution for managing vast amounts of data. The paper highlights cloud computing's benefits in data processing, device management, cost efficiency and scalability. However, challenges related to security, data ownership, and vendor lock-in require attention. A novel sustainable cloud-IoT model is presented by integrating smart computing with cloud infrastructure. It is observed that the model records promising performance. The mean response delay is 1.9 seconds and the 89.5% is the generated mean computational storage accuracy rate. In conclusion, the cloud computing empowered sustainable model can be used in organizations to gain insights from IoT data and make informed decisions, shaping future research in this rapidly evolving field. 2023 IEEE.
Sharma A.; Kumari A.; Sharma V.; Al-Farouni M.; Mishra S.
International Conference for Technological Engineering and its Applications in Sustainable Development, ICTEASD 2023, pp. 86-91.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICTEASD57136.2023.10585245 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199548771&doi=10.1109%2fICTEASD57136.2023.10585245&partnerID=40&md5=b0eebfcd7489019c319d4cca9befb523
Sharma A., Deemed to Be University, Kalinga Institute of Industrial Technology, India; Kumari A., Deemed to Be University, Kalinga Institute of Industrial Technology, India; Sharma V., CHRIST (Deemed to Be University), Delhi NCR, India; Al-Farouni M., The Islamic University, College of Technical Engineering, Najaf, Iraq; Mishra S., Deemed to Be University, Kalinga Institute of Industrial Technology, India
Deep Learning Character Recognition of Handwritten Devanagari Script: A Complete Survey
Character Recognition; Computer Vision; Deep Learning; Pattern Recognition
Recognition of handwritten characters is a concept in which the single characters are classified, it is a facility of an electronic device to scan and decipher the handwritten input from a variety of sources, including written texts, images, and other digital touch-screen devices. This concept is being used in distinctive sectors such as the processing of bank checks, form data entry, and parcel posting and nowadays it is becoming a very important issue in the pattern recognition domain and a very challenging task to resolve it. Since deep learning is a crucial strategy in solving detection and pattern recognition problems, several algorithms are available to classify the characters with better prediction rates on different datasets, and ultimately, whichever algorithm gives the optimized results will be considered the best solution for the character recognition problem. As a result, various solutions proposed by the existing researchers are discussed using deep learning algorithms in this survey article. 2023 IEEE.
Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications
Sharma A., CHRIST(Deemed to Be University), Department of Computer Science, and Engineering, Bangalore, India; Mithun B.N., CHRIST(Deemed to Be University), Department of Computer Science, and Engineering, Bangalore, India
A Comparative Investigation on the use of Machine Learning Techniques for Currency Authentication
Currency Authentication; Data mining; K-means clustering; Random Forest; Support Vector Machine; unsupervised learning. Supervised Learning
In the present banking sector, identifying the real and the fake note is a very challenging task because if we do it manually, it takes a long time to check which is real and which is fake. This research study article aims to authenticate the money between real and fake by using different machine algorithms facilitating learning, such as K-means Clustering, Random Forest Classification, Support Vector Machines, and logistics Regression. Specifically, we consider the banknote dataset. The data of money is extracted from various banknote images by using the wavelet transform tool, which is primarily used to remove elements from the images. However, we are mainly concerned with the different machine learning algorithms, so we take the two variables, where the first variable indicates image variance and the second indicates image skewness. We use these two variables to train our machine learning algorithms. So, majorly, by applying the different machine learning algorithms, which are supervised and unsupervised, we find the accuracy for the respective machine learning algorithms and then visualize and classify the real and fake notes separately. Finally, the prediction is based on integrity, which means the efficiency value is based on how much the mechanism system can uncover the fake notes. Then, after calculating the accuracy of currency authentication, there is a high possibility that the accuracy of the particular algorithm is the best algorithm, so the application of currency authentication will be very useful for the bank to easily find duplicate notes. 2022 IEEE.
2022 1st International Conference on Artificial Intelligence Trends and Pattern Recognition, ICAITPR 2022
https://doi.org/10.1109/ICAITPR51569.2022.9844207 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136824363&doi=10.1109%2fICAITPR51569.2022.9844207&partnerID=40&md5=ffe960edb89ad4b8cf47f920e915bdc8
Sharma A., CHRIST(Deemed to Be University), Computer Science and Engineering, Bangalore, India; Prathap B.R., CHRIST(Deemed to Be University), Computer Science and Engineering, Bangalore, India; Hussain J., CHRIST(Deemed to Be University), Computer Science and Engineering, Bangalore, India
Two inventory models for growing items under different payment policies with deterioration
delay in payment; deteriorating items; growing items; inventory management; mortality
Industries of growing items show an upward trend in the production as well as in consumption. Poultry and livestock are good examples of growing items which are both deteriorating and ameliorating in nature. In this study apart from these specific features of growing items, one of the real-world business policies, permission of delay in payment is also considered. Present paper proposed two inventory models, one with the permission of delay in payment and another without it. Concavity of the profit functions with respect to decision variables are discussed analytically for both the models. Solution procedure and numerical examples are provided in order to get the managerial insights. The numerical analysis growth in weight is approximated by Richard's growth function. The numerical analysis predicts that net profit and the initial purchase quantity both increases under the permissible delay payment policy compared to without it. Sensitivity analysis provides important managerial insights. Copyright 2022 Inderscience Enterprises Ltd.
International Journal of Procurement Management, Vol-15, No. 4, pp. 447-462.
https://doi.org/10.1504/IJPM.2022.123189 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131442503&doi=10.1504%2fIJPM.2022.123189&partnerID=40&md5=fb76e3a56912b6c4721a7d3ce3c4fec1
Sharma A., School of Sciences, CHRIST (Deemed to be University), Delhi-NCR, Ghaziabad, 201003, India; Saraswat A.K., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India
Optimal procurement and pricing policy for deteriorating items with price and time dependent seasonal demand and permissible delay in payment
delay payment; deterioration; Inventory; price and time dependent demand; seasonal demand
In practice, items like food, nursery plants, medicines, etc. are seasonal and deteriorating in nature. For this type of products, permissible delay in payment is a common business policy, which is used to increase in the sell volume and to develop trust in buyer-seller relationship. In this paper, we developed an inventory model for time dependent deteriorating seasonal items with the permission of delay in payment. Shortages are permitted and partially back ordered. Our aim is to find optimal selling price and ordering quantity simultaneously. Concavity of profit function with respect to decision variables has been discussed analytically. A solution procedure followed by a numerical example and sensitivity analysis along with managerial insights are provided. Numerical analysis predicts that delay in payment profit policy is a better decision in order to maximise the profit or in order to get more profit. 2022 Inderscience Enterprises Ltd.
International Journal of Mathematics in Operational Research, Vol-21, No. 4, pp. 515-528.
https://doi.org/10.1504/IJMOR.2022.122802 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130552055&doi=10.1504%2fIJMOR.2022.122802&partnerID=40&md5=8800fd1c8060547a440dadfc97a24416
Sharma A., School of Sciences, CHRIST (Deemed to Be University), Delhi-NCR, Ghaziabad, 201003, India; Saraswat A.K., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India
Profit function Optimization for Growing Items Industry
constant demand; delay in payment; economic ordering quantity model; Growing items; mortality
The economy of a country depends on many industries; growing item industries are one of them. Growing items also exhibit mortality in the growth period, which creates a complex environment for the procurement decision. A practical inventory model is required to overcome this situation, which provides the optimum solution. This work describes an economics ordering quantity model for growing items with constant demand and mortality. We also take into consideration that one of the real-life management practices for businesses is the allowance of a delay in payment. There is a solution procedure with a numerical example. We have discussed analytical results to verify the concavity of the profit function. Sensitivity analysis provides us with some very useful information. . 2023 IEEE.
2023 6th International Conference on Information Systems and Computer Networks, ISCON 2023
https://doi.org/10.1109/ISCON57294.2023.10111991 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159463802&doi=10.1109%2fISCON57294.2023.10111991&partnerID=40&md5=198c13a98b3d096a9bbd083e8effafe8
Sharma A., Christ (Deemed to Be University), Delhi-NCR, School of Sciences, Ghaziabad, 201003, India, Institute of Applied Sciences and Humanities, GLA University, Department of Mathematics, NH-2, Mathura, 281406, India; Saraswat A.K., Christ (Deemed to Be University), Delhi-NCR, School of Sciences, Ghaziabad, 201003, India, Institute of Applied Sciences and Humanities, GLA University, Department of Mathematics, NH-2, Mathura, 281406, India
An Inventory Model for Growing Items with Deterioration and Trade Credit
Delay in payment; Deteriorating items; Growing items; Inventory management; Mortality; Price dependent demand
Growing items industry plays a vital role in the economy of most of the countries. Growing item industries consists of live stocks like sheep, fishes, pigs, chickens etc. In this paper, we developed a mathematical model for growing items by considering various operational constraints. The aim of the present model is to optimize the net profit by optimizing decision variables like time after growing period and shortages. Also, the delay in payment policy has been used to maximize the profit. A numerical example is provided in support of the solution procedure. Sensitivity analysis provides some important insights. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Networks and Systems, Vol-290, pp. 232-238.
Efficient cationic dye removal from water through Arachis hypogaea skin-derived carbon nanospheres: a rapid and sustainable approach
The present study investigates the potential of Arachis hypogaea skin-derived carbon nanospheres (CNSs) as an efficient adsorbent for the rapid removal of cationic dyes from aqueous solutions. The CNSs were synthesized through a facile, cost-effective, catalyst-free and environmentally friendly process, utilizing Arachis hypogaea skin waste as a precursor. This is the first reported study on the synthesis of mesoporous carbon nanospheres from Arachis hypogaea skin. The structural and morphological characteristics of the CNSs were confirmed by different nano-characterization techniques. The adsorption performance of the carbon nanospheres was evaluated through batch adsorption experiments using two cationic dyes-methylene blue (MB) and malachite green (MG). The effects of the initial dye concentration, contact time, adsorbent dosage, and pH were investigated to determine the optimal conditions for dye removal. The results revealed that the obtained CNSs exhibited remarkable adsorption capacity and rapid adsorption kinetics. Up to ?98% removal efficiency was noted for both dyes in as little as 2 min for a 5 mg L?1 dye concentration, and the CNSs maintained their structural morphology even after adsorption. The adsorption data were fitted to various kinetic and isotherm models to gain insights into the adsorption mechanism and behaviour. The pseudo-second-order kinetic model and Redlich-Peterson model best described the experimental data, indicating multi-layer adsorption and chemisorption as the predominant adsorption mechanism. The maximum adsorption capacity was determined to be 1128.46 mg g?1 for MB and 387.6 mg g?1 for MG, highlighting the high affinity of the carbon nanospheres towards cationic dyes. Moreover, CNS reusability and stability were examined through desorption and regeneration experiments, which revealed sustained efficiency over 7 cycles. CNSs were immobilised in a membrane matrix and examined for adsorption, which demonstrated acceptable efficiency values and opened the door for further improvement. 2024 RSC.
Sharma A.; Shivanna J.M.; Alodhayb A.N.; Hegde G.
Nanoscale Advances, Vol-6, No. 12, pp. 3199-3210.
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.1039/d4na00254g https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193331463&doi=10.1039%2fd4na00254g&partnerID=40&md5=c8856f21b264a8dd12ce8e97fc3b7e72
Sharma A., Department of Chemistry, School of Sciences, CHRIST, Deemed to be University, Hosur Road, Bengaluru, 560029, India, Centre for Advanced Research and Development (CARD), CHRIST, Deemed to be University, Hosur Road, Bengaluru, 560029, India; Shivanna J.M., Department of Chemistry, AMC Engineering College, Bannerghatta Road, Bengaluru, 560083, India; Alodhayb A.N., Department of Physics and Astronomy, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia; Hegde G., Department of Chemistry, School of Sciences, CHRIST, Deemed to be University, Hosur Road, Bengaluru, 560029, India, Centre for Advanced Research and Development (CARD), CHRIST, Deemed to be University, Hosur Road, Bengaluru, 560029, India
Exploring the efficiency of green synthesized silver nanoparticles as photocatalysts for organic dye degradation: unveiling key insights
AgNPs; biosynthesis; dye degradation; green synthesis; photocatalysis; silver nanoparticles
Silver nanoparticles (AgNPs) have received a lot of interest for their several applications, including their remarkable potential as photocatalysts for organic dye degradation. This research thoroughly investigates the efficacy of ecologically friendly, green-synthesized AgNPs in the treatment of synthetic dye-contaminated wastewater. The synthesis of AgNPs from various biological substrates is investigated, emphasizing their economic viability, significant conductivity, and considerable biocompatibility. The improper disposal of synthetic dyes in wastewater poses severe environmental and health risks due to their non-biodegradable nature and persistent chemical features. In response to this challenge, this review paper investigates the capability of AgNPs to serve as effective photocatalysts for degrading a range of organic dyes commonly found in industrial effluents. Specific dyes, including methyl orange, congo red, nitrophenol, methylene blue, and malachite green, are studied in the context of wastewater treatment, providing insights into the efficacy of AgNPs synthesized from diverse biological sources. The review sheds light on the photocatalytic degradation methods used by green-synthesized AgNPs, shedding light on the transition of these synthetic dyes into less hazardous compounds. It also delves into the toxicity aspect of the AgNPs and its possible remediation from the environment. The ecologically friendly synthesis procedures investigated in this work provide an alternative to traditional methods, highlighting the importance of sustainable technologies in solving modern environmental concerns. Furthermore, a comparative examination of various biological substrates for AgNPs synthesis is presented, evaluating their respective dye degradation efficiencies. This not only helps researchers understand the environmental impact of synthetic dyes, but it also directs them in choosing the best substrates for the production of AgNPs with enhanced photocatalytic activities. 2024 The Author(s). Published by IOP Publishing Ltd.
Sharma A.; Sunny S.; Arulraj J.; Hegde G.
https://doi.org/10.1088/2632-959X/ad4d09 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195105589&doi=10.1088%2f2632-959X%2fad4d09&partnerID=40&md5=3a1eaf77697fd490a03be109b2b7d1da
Sharma A., Department of Chemistry, School of Sciences, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India, Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Sunny S., Department of Chemistry, School of Sciences, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Arulraj J., Department of Chemistry, School of Sciences, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Hegde G., Department of Chemistry, School of Sciences, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India, Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India
Brain Tumor Classification: A Comparison Study CNN, VGG 16 and ResNet50 Model
Accuracy; Brain tumor; CNN; Custom CNN; ResNet50; VGG 16
Brain tumors pose a severe threat to global health and may be lethal. Early detection and classification of brain tumors are essential for successful therapy and better patient outcomes. The good news is that advances in deep learning techniques have shown tremendous promise in medical image analysis, particularly in the detection and classification of brain tumors. Convolutional Neural Networks (CNN), a class of deep learning models, are used to process and analyze visual input, notably images, and movies. They excel in computer vision tasks like object detection, image segmentation, and categorization. Popular and efficient image analysis methods include CNNs. VGG 16 and ResNet 50 are two examples of deep convolutional neural network architectures used for image categorization applications. A number of image identification problems have been successfully solved using the 16 layer VGG 16. ResNet50, a well known 50 layer architecture, employs residual connections to get over the vanishing gradient issue and permits the training of deeper networks. A proprietary CNN model, VGG 16, and ResNet50 were compared in studies to see how well they performed on a dataset. The VGG 16, ResNet50, and the tailored CNN model were the most precise models. As a consequence, VGG 16 accurately detects brain cancers in the dataset that was supplied. Overall, this study highlights the value of deep learning techniques for medical image processing and their potential to improve the accuracy and efficacy of brain tumor diagnosis and treatment. 2023 IEEE.
Sharma A.; Zehra A.; Das A.; Rastogi K.; Agarwal M.; Mascarenhas S.; Jayapriya J.; Vinay M.; Deepa S.
2023 International Conference on Data Science and Network Security, ICDSNS 2023
Sharma A., Christ University, Department of Computer Science, Bengaluru, India; Zehra A., Christ University, Department of Computer Science, Bengaluru, India; Das A., Christ University, Department of Computer Science, Bengaluru, India; Rastogi K., Christ University, Department of Computer Science, Bengaluru, India; Agarwal M., Christ University, Department of Computer Science, Bengaluru, India; Mascarenhas S., Christ University, Department of Computer Science, Bengaluru, India; Jayapriya J., Christ University, Department of Computer Science, Bengaluru, India; Vinay M., Christ University, Department of Computer Science, Bengaluru, India; Deepa S., Christ University, Department of Computer Science, Bengaluru, India
Pattern Recognition: An Outline of Literature Review that Taps into Machine Learning to Achieve Sustainable Development Goals
Artificial intelligence; Lower costs; Machine learning; Pattern recognition; SDGs; Sustainability; Sustainable development
The sustainable development goals (SDGs) as specified by the United Nations are a blueprint to make the Earth to be more sustainable by the year 2030. It envisions member nations fighting climate change, achieving gender equality, quality education for all, and access to quality healthcare among the 17 goals laid out. To achieve these goals by the year 2030, member nations have put special schemes in place for citizens while experimenting with newer ways in which a measurable difference can be made. Countries are tapping into ancient wisdom and harnessing newer technologies that use artificial intelligence and machine learning to make the world more liveable. These newer methods would also lower the cost of implementation and hence would be very useful to governments across the world. Of much interest are the applications of machine learning in getting useful information and deploying solutions gained from such information to achieve the goals set by the United Nations for an imperishable future. One such machine learning technique that can be employed is pattern recognition which has applications in various areas that will help in making the environment sustainable, making technology sustainable, and thus, making the Earth a better place to live in. This paper conducts a review of various literature from journals, news articles, and books and examines the way pattern recognition can help in developing sustainably. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Lecture Notes in Networks and Systems, Vol-868, pp. 89-100.
Sharma A.M., Symbiosis Centre for Management Studies, Bengaluru Campus, Symbiosis International (Deemed University), Pune, India; Arumugam S.K., Christ University, Bangalore, 560029, India
Study to assess attitudes towards statistics of business school students: An application of the SATS-36 in India
Attitude; Business education; Curriculum; Factor analysis; Post-test; Pre-test; SATS-36; Statistics education
Students attitudes towards Statistics are pivotal to their learning process as positive attitudes lead to highly satisfactory course achievement and lead to positive outcomes outside class as well. In this paper we are exploring the perception of students of management apropos Statistics, familiarity with which is imperative in todays world of Analytics. The quantitative approach was used to compare attitudes of the students using the two versions of the SATS-36 instrument validated and copyrighted by Candace Schau. A Google form was used to collect responses and was sent to all the students who were enrolled in the Business Statistics course. 172 students responded for the pre-test study while 71 students responded for the post-test study. Data was analysed to see if gender, specialisation choices and previous math experiences accounted for differences in perceptions towards Statistics. It was found that students overall perception of statistics is positive and surprisingly they were more positive towards the beginning of the semester. These results are important as they can lead towards understanding of business students attitudes towards statistics and a way to refine the teaching learning process so that students are in a strong position to exploit the supply demand gap in the Analytics domain and deliver value to organisations. 2021 Eskisehir Osmangazi University. All rights reserved.
International Journal of Instruction, Vol-14, No. 3, pp. 207-222.
Gate Association for Teaching and Education
https://doi.org/10.29333/iji.2021.14312a https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109635079&doi=10.29333%2fiji.2021.14312a&partnerID=40&md5=e23f0fbaec0afe1ee04237a62848a187
Sharma A.M., Department of Professional Studies, Christ University, Karnataka, Bengaluru, 560029, India; Srivastav A., Mumbai, India
A ratiometric luminescence thermometer based on lanthanide encapsulated complexes
Lanthanide-containing complexes have been widely developed as ratiometric luminescence thermometers, which are non-invasive, contactless and accurate. The synthesis of these Ln complexes generally requires high temperatures, multiple steps and other harsh conditions. Moreover, bimetallic lanthanide complexes, which have been reported to be better thermometers, are even more challenging to synthesize. This complexity can be simplified by preparing a host-guest complex of lanthanides. In this work, Tb or both Tb and Eu are encapsulated in an MOF host, making them emissive. The ratio of Tb/Eu was also easily tuned by simply changing their ratio in the solution, resulting in a tunable emission. Accordingly, we were able to synthesise both the emissive Tb complex and Tb/Eu complexes at different ratios using a single host. The complexes were found to be suitable as ratiometric luminescent thermometers in the temperature range of 160-380 K, with reasonably good sensitivity and uncertainty. The thermometer's sensitivity and uncertainty were significantly improved using bimetallic Tb and Eu host-guest complexes. Calculations using the host and Eu emission ratio were found to provide better thermometer parameters than the commonly reported Tb and Eu emission ratio. Thus, using a single host, we were able to synthesise different lanthanide complexes that can sense temperature, and we improved the thermometer parameters by incorporating multiple lanthanides in a single host. This research will enable the scientific community to reexamine the applicability of unexplored host-guest lanthanide complexes. 2025 The Royal Society of Chemistry.
Sharma A.R.; Singh A.R.; Kongasseri A.A.; Garain S.; Mariella Babu A.; Lonibala R.; Laishram R.
Dalton Transactions, Vol-54, No. 4, pp. 1377-1383.
ISSN: 14779226; PubMed ID: 39523808; CODEN: DTARA
https://doi.org/10.1039/d4dt02639j https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209395173&doi=10.1039%2fd4dt02639j&partnerID=40&md5=df571d8c5c122ab8962d40221a761a6b
Sharma A.R., Department of Chemistry, Manipur University, Manipur, 795003, India; Singh A.R., Department of Chemistry, Manipur University, Manipur, 795003, India; Kongasseri A.A., New Chemistry Unit and School of Advanced Materials, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR) Jakkur, Bangalore, 560064, India; Garain S., University of Wzburg, Wzburg, Germany; Mariella Babu A., Christ University, Bengaluru, 560029, India; Lonibala R., Department of Chemistry, Manipur University, Manipur, 795003, India; Laishram R., Department of Chemistry, Manipur University, Manipur, 795003, India
Powering Ahead: Navigating Opportunities and Challenges in the Electric Vehicle Revolution
The technology is clearing ways for buzz in the market brimming with innovative items and new prospects. The government has planned to shift to electric vehicles by 2030, whether it is for personal or commercial use. As innovative improvements are developing quickly, it is blasting the market with the EVs industry which expected to transform the future (Rajkumar S, in Indian electric vehicle conundrum: a tale of opportunities amid uncertainties, 2020). Volvo company has also announced that it will be fully electric by 2030 (https://gadgets.ndtv.com, in Volvo to go all electric by 2030, sell exclusively online, 2021). It is expected that EVs will generate more demand for electricity and help in settling the focus on resources problem. It will also help in improving the financial feasibility of power sector projects. In India, there is more dependency on renewable energy so this is a chance to be independent and provide cheap power to the people. The EVs are more economical than petrol or diesel vehicles. The government is also giving incentives to the makers of electric vehicles. GST on electric vehicles is 12% as compared to petrol and diesel vehicles with 28% GST. As per the Electricity Act, 2003, a distribution license is needed to supply power from respective state electricity regulatory commissions. Another challenge is that charging the EVs will lead to a rise in the demand of electricity which is risky for the electricity distribution companies (www.livemint.com, in Indias electric vehicle drive: challenges and opportunities, 2017). Indians are very price conscious. A recent study revealed that Indians are ready to compromise on more charging time, but they are not ready to pay higher price for EVs (Gupta NS, in Electric vehicle adoption in India: study reveals three tipping points, 2020). From Fig.1, it can be seen that in 2014 investment in EVs was $2.2 billion which has increased to $406 billion in 2019 (Shanti S, in The road to green: what makes electric vehicle adoption a challenge for India. 2020). This shows that people are shifting toward EVs. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Lecture Notes in Electrical Engineering, Vol-1162, pp. 643-649.
Sharma B., School of Commerce, Finance and Accountancy, Christ University, Karnataka, Bangalore, India
Responding to the pandemic: A case of the indian hotel industry
The chapter presents a case study on how Indian hotel industry was affected by COVID-19. Three hotels-Lemon Tree, Oyo Rooms, and Taj Hotels-were selected to elaborate. The study found that the hotel industry developed various policies to keep running their hotels during the pandemic. Lemon Tree joined various hospitals to provide rooms to COVID patients, provided free food and face masks to individuals. Oyo Rooms gave employee stock ownership plans of Rs 130 crore to its COVID-hit employees. Taj Hotels did not cut down the salaries of their employees and reduced its seating capacity by 50%. The study concluded that as the hospitality sector battled hard to continue during the pandemic, modernization would become an imperative tool in the post-COVID period to beat obstructions and spotlight advancement. So, the companies should minimize fixed costs and maximize variable costs. They should preferably have liquid cash available that could enable them to mitigate the risk. 2022, IGI Global.
Sharma B.; Budhiraja A.; Singh S.; Bala R.
Cases on Emerging Market Responses to the COVID-19 Pandemic, pp. 126-143.
Sharma B., Department of Commerce, JIMS Engineering Management Technical Campus, Greater Noida, India; Budhiraja A., Department of Commerce, JIMS Engineering Management Technical Campus, Greater Noida, India; Singh S., School of Commerce, Finance, and Accountancy, Christ University, India; Bala R., Mukhtiar Singh Memorial Degree College, Haryana, India
EVALUATION OF THE ENVIRONMENTAL EFFECTS OF MEDICAL WASTE AND ITS INCREASE AFTER COVID-19 PANDEMIC
environmental impact; groundwater pollution; hazardous waste; heavy metals and mitigation strategies; improper disposal; medical waste; public health
Medical waste is a special course of harmful contaminants. Improper treatment would cause tributary environmental pollution, expressly when countering to communal health tragedies. However, there are quite few explores on the peer group of medical waste, and there is a deficiency of basic considerate of its spatial-temporal heterogeneity. The purpose of this study is to conduct a systematic estimation of the effectiveness of these incongruous discarding procedures in expressions of water eminence and wellbeing. The research is centred on municipal areas characterised by vital medical waste production, which has the probable to taint groundwater and water sources. A complex approach is exploited in the procedure, which comprises of water sample collection, laboratory analysis, field surveys, and GIS-based spatial mapping. Medical waste disposal hotspots, such as healthcare facilities, waste collection points, and disposal sites, will be acknowledged through field surveys. Inspects will be showed on water samples poised from a variability of sources, including lakes, rivers, and groundwater wells, to find pathogens, medical residues, heavy metals, and organic pollutants, which are all gauges of medical waste contamination. The test centre analysis will utilise chic policies to portion the deliberation of pollutants in water samples, thereby gauging the likely hazards they pose to marine ecosystems and human health. Longitudinal visualisation of uncleanness distribution through GIS-based mapping facilitates the credentials of vulnerable areas and potential pathways for pollutant transport. The findings of this research will offer significant helps to our understanding of the extent of environmental deterioration resulting from the inadequate disposal of medical refuse into urban water sources. The results of this study will provide valuable insights for the creation of alertness campaigns, regulatory frameworks, and mitigation strategies that are operative in talking this urgent environmental concern and shielding the truthfulness of water in municipal regions. 2024, Scibulcom Ltd.. All rights reserved.
Sharma B.; Sailaja M.; Bansal R.; Soujanya K.; Nerlekar T.; Acharjee P.B.; Rajagopal R.
Journal of Environmental Protection and Ecology, Vol-25, No. 6, pp. 1833-1845.
Sharma B., Geeta University, Panipat, India; Sailaja M., Department of CSE, Ravindra College of Engineering for Women, Kurnool, India; Bansal R., Department of Mittal School of Business, Lovely Professional University, Punjab, Phagwara, India; Soujanya K., Department of BBA, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, Guntur, India; Nerlekar T., Department of Civil Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, India; Acharjee P.B., Department of Computer Science, CHRIST University, Bangalore, India; Rajagopal R., Department of Computer Science and Engineering, Alliance School of Advanced Computing, Alliance University, Karnataka, Bengaluru, India