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Computational Modelling of Complex Systems for Democratizing Higher Education: A Tutorial on SAR Simulation
Engineering systems like Synthetic Aperture Radar (SAR) are complex systems and require multi-domain knowledge to understand. Teaching and learning SAR processing is intensive in terms of time and resources. It also requires software tools and computational power for preprocessing and image analysis. Extensive literature exists on computational models of SAR in MATLAB and other commercial platforms. Availability of computational models in open-source reproducible platforms like Python kernel in Jupyter notebooks running on Google Colaboratory democratizes such difficult topics and facilitates student learning. The model, discussed here, generates SAR data for a point scatterer using SAR geometry, antenna pattern, and range equation and processes the data in range and azimuth with an aim to generate SAR image. The model demonstrates the generation of synthetic aperture and the echo signal qualities as also how the pulse-to-pulse fluctuating range of a target requires resampling to align the energy with a regular grid. The model allows for changing parameters to alter for resolution, squint, geometry, radar elements such as antenna dimensions, and other factors. A successful learning outcome would be to understand where parameters need to be changed, to affect the model in a specific way. Factors affecting Range Doppler processing are demonstrated. Use of the discussed model nullifies use of commercial software and democratizes SAR topic in higher education. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Deep Learning Based Performance Prediction of Sustainable Microwave Absorbers
This paper proposed a convolutional neural network (CNN) based deep learning (DL) approach to predict performance of sustainable microwave absorbers. This study explores the transformative potential of DL in predicting and optimizing microwave absorber performance, offering a datadriven alternative to traditional approaches. The absorber is a composite of tea and carbon powder considered as waste mixed in various composition percentages. The measured S21 data is used for training the proposed DL model. The prediction of absorber's S21 performance shows an accuracy of above 98 %. 2025 IEEE. -
Novel preemptive intelligent artificial intelligence-model for detecting inconsistency during software testing
The contribution of artificial intelligence (AI)-based modelling is highly significant in automating the software testing process; thereby enhancing the cost, resources, and productivity while performing testing. Review of existing AI-models towards software testing showcases yet an open-scope for further improvement as yet the conventional AI-model suffers from various challenges especially in perspective of test case generation. Therefore, the proposed scheme presents a novel preemptive intelligent computational framework that harnesses a unique ensembled AI-model for generating and executing highly precise and optimized test-cases resulting in an outcome of adversary or inconsistencies associated with test cases. The ensembled AI-model uses both unsupervised and supervised learning approaches on publicly available outlier dataset. The benchmarked outcome exhibits supervised learning-based AI-model to offer 21% of reduced error and 1.6% of reduced processing time in contrast to unsupervised scheme while performing software testing. 2025, Institute of Advanced Engineering and Science. All rights reserved. -
Novel artificial intelligence-based ensemble learning for optimized software quality
Artificial intelligence (AI) contributes towards improving software engineering quality; however, existing AI models are witnessed to deploy learning-based approaches without addressing various complexities associated with datasets. A literature review showcases an unequilbrium between addressing the accuracy and computational burden. Therefore, the proposed manuscript presents a novel AI-based ensemble learning model that is capable of performing an effective prediction of software quality. The presented scheme adopts correlation-based and multicollinearity-based attributes to select essential feature selection. At the same time, the scheme also introduces a hybrid learning approach integrated with a bio-inspired algorithm for constructing the ensemble learning scheme. The quantified outcome of the proposed study showcases 65% minimized defect density, 94% minimized mean time to failure, 62% minimized processing time of the algorithm, and 43% enhanced predictive accuracy. 2025, Institute of Advanced Engineering and Science. All rights reserved. -
RayleighBard and BardMarangoni magnetoconvection in variable viscosity finitely conducting liquids
The thermorheological effect on magneto-Bard-convection is studied numerically in fluids with finite electrical conductivity. A nonlinear thermorheological equation is considered in the problem. The results are compared with the classical approach of constant viscosity, which depicts the fact that the effect of increasing the strength of the magnetic field is to delay the onset of convection. The magnetic field is shown to have a rheostatic influence on convective instabilities. The results obtained by the study have possible applications in the field of astrophysics, sunspots, and in space applications under microgravity. 2021 Wiley Periodicals LLC -
Sulfamic acid catalyzed grinding: A facile one-pot approach for the synthesis of polysubstituted pyrazoles under green conditions
A competent, rapid and simple grinding procedure for the synthesis of pharmacologically relevant polysubstituted pyrazoles catalyzed by sulfamic acid is reported via multicomponent reaction of substituted arylaldehydes, 4-nitrophenylacetonitrile, hydrazine hydrate, ethyl acetoacetate under solvent-free reaction conditions. In our reported protocol, four different reactants featuring diverse functional groups are assembled in one pot, enabling the synthesis of more diverse molecular structures in a facile manner. 2022 -
Mn2(CO)10 catalyzed visible-light-promoted synthesis of 1H-pyrazole-4-carboxamides; A sustainable multi-component statergy with antibacterial and cytotoxic evaluations
Multicomponent reactions play a pivotal role in synthesizing 1H-pyrazole-4-carboxamides, underscoring its significance in sustainable organic synthesis. These compounds, valued for their diverse biological activities, have garnered substantial attention in pharmaceutical research. A facile, rapid one-pot strategy to access an extensive array of 1H-pyrazole-4-carboxamide derivatives, utilizing substituted aldehydes, cyanoacetamide, and hydrazine hydrate as substrates and a readily accessible Mn2(CO)10 as photocatalyst in EL: H2O (1:1). Among the synthesized series, products 4b, 4 g, 4k showed remarkable antibacterial activity against E coli, P aeruginosa, S. aureus in agar medium and excellent cytotoxicity with Human colorectal carcinoma (HCT-116), Liver cancer cells (Hep-G2) and breast adenocarcinoma (MCF-7) cell lines. The current method is characterized by its affordability, non-toxicity, easy access to starting materials, and notably with minimal waste generation. Additionally, remarkable aspects include its mild operating conditions, environmentally friendly nature, and the ability to accommodate a wide range of both electron-donating and electron-withdrawing groups. 2024 The Author(s) -
Visible Light Mediated Organophotoredox-Catalyzed One-Pot Domino Synthesis of Novel 6,7 Disubstituted 1H-Pyrroles
The development of environmentally benign protocols to synthesize novel N-heterocycles is vital in the field of synthetic organic chemistry. We herein report a successful one-pot domino synthesis of novel 6,7 disubstituted 1H-pyrroles using substituted phenacyl bromide, barbituric acid/Meldrums acid, aromatic amines catalysed by 5mol% Fluorescein in presence of visible light. This procedure is a useful and adaptable method for the synthesis of pyrroles since it is compatible with a wide range of sensitive functional groups, does not require column chromatography purification. During the reaction, Fluorescein may catalyse the formation of enamine leading to amino alcohol which subsequently undergoes dehydration to give 6,7 disubstituted 1H-pyrroles. All the synthesized derivatives were obtained in 9095% yields and were characterized by 1H, 13C NMR and HRMS (ESI) analysis. Graphical Abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Sulphuric acid supported silica gel (H2SO4-SiO2) as an efficient catalyst for one-pot multicomponent synthesis of pyrano[2,3-c]pyrazol-amines under ultrasonication
In this study, the catalytic potential of a novel heterogeneous catalyst-sulphuric acid supported on silica gel (H2SO4-SiO2) has been assessed for the one-pot cyclo condensation reaction of aromatic aldehydes, 4-nitrophenylacetonitrile, ethyl acetoacetate and hydrazine/phenyl hydrazine to furnish poly functionalized pyrano[2,3-c]pyrazol-amine scaffolds under ultrasonication. Notably, within the framework of green chemistry, this divergent and step-economic approach has many benefits such as (i) use of water as solvent in the reaction, (ii) creation of up to five bonds in one sequence, (iii) avail of US irradiation as an efficient source of energy, (iv) application of nontoxic and reusable catalyst. Besides these, simple workup procedure, low catalyst loadings, shorter reaction time, high functional group compatibility, readily accessible starting materials and excellent yields without column chromatography render this protocol novel and greener towards the synthesis of poly functionalized pyrano[2,3-c]pyrazol-amines. 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Second International Symposium ''Functional Nanomaterials in Industrial Applications: Academy - Industry Meet''. -
Citric-Acid-Catalyzed Green and Sustainable Synthesis of Novel Functionalized Pyrano[2, 3-e]pyrimidin- and Pyrano[2, 3-d]pyrazol-amines in Water via One-Pot Multicomponent Approaches
An efficient entry into the preparation of elusive, novel pyrano[2, 3-e]pyrimidin-amines and pyrano[2, 3-d]pyrazol-amines has been accomplished using citric acid as a green catalyst in aqueous medium at 25 C. The strategy successively tolerates a variety of functional groups and interestingly, it is eco-compatible, environment-friendly, propitious and the products are obtained in excellent yields without chromatographic purification. The current methodology unfolds the benefits of citric acid as an effective, expeditious, economical, green catalyst and thus adheres to the principles of green chemistry. Ecstatically, the reaction was scaled to the gram level ascertaining the wide applicability of the protocol in academia and industry. The green metrics (E-factor: 0.0497, Mass intensity: 1.1022, PMI: 1.0497 and Emw: 0.0497) for the reaction was also envisaged and the pathway was found to acquaint excellent green chemistry metrics. 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim -
Visible Light Mediated Organophotoredox-Catalyzed One-Pot Domino Synthesis of Novel 6,7 Disubstituted 1H-Pyrroles
The development of environmentally benign protocols to synthesize novel N-heterocycles is vital in the field of synthetic organic chemistry. We herein report a successful one-pot domino synthesis of novel 6,7 disubstituted 1H-pyrroles using substituted phenacyl bromide, barbituric acid/Meldrums acid, aromatic amines catalysed by 5mol% Fluorescein in presence of visible light. This procedure is a useful and adaptable method for the synthesis of pyrroles since it is compatible with a wide range of sensitive functional groups, does not require column chromatography purification. During the reaction, Fluorescein may catalyse the formation of enamine leading to amino alcohol which subsequently undergoes dehydration to give 6,7 disubstituted 1H-pyrroles. All the synthesized derivatives were obtained in 9095% yields and were characterized by 1H, 13C NMR and HRMS (ESI) analysis. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. -
Investigating key biological traits of Malva parviflora influencing its competitive invasion in wheat crops
Plant invasion is a major concern for ecologists and agriculturists. Early detection of potential invaders (weeds) would save energy and resources that would otherwise be used to tackle them after they had spread. A study was initiated at the ICAR-Indian Agricultural Research Institute, New Delhi, on the basis of the early detection and rapid response (EDRR) strategy. For this study, we choose the little mallow (Malva parviflora L.), a newly introduced Malvaceae family weed in the agricultural fields of Delhi and adjoining regions of India. The above-ground allometric parameters ofM. parviflora populations in the main field and the field boundary were compared. The findings revealed that the EDRR approaches established by this study provided useful information to corroborate the weed species' invasion. The canopy diameter, plant height, and the number of leaves M. parviflora differed between the field boundaries (25.72cm, 24.40cm, 58.97, respectively) and main field (12.79cm, 49.08cm, 18.85, respectively) populations in all three locations, except the canopy diameter was comparable in location 2. Furthermore, neighborhood analysis showed that the M. parviflora had greater acclimatization with a variety of neighbors (38 plant species), i.e., legumes, noxious weeds, and seasonal dominant weeds. Malva parviflora has become a dominant weed along the field boundary. However, it has the potential to spread to the main field and become a serious weed in winter crops in the future. The EDRR methodologies developed in this study can be used to assess the invasion of new weeds in a variety of habitats. Plant Science and Biodiversity Centre, Slovak Academy of Sciences (SAS), Institute of Zoology, Slovak Academy of Sciences (SAS), Institute of Molecular Biology, Slovak Academy of Sciences (SAS) 2025. -
Comparative Analysis and Development of Recommendations for the Use of Machine Learning Methods to Identify Network Traffic Anomalies in the Development of a Subsystem for User Behavioral Analysis
This article discusses various machine learning methods in order to conduct a more effective analysis of user network traffic using a subsystem for analyzing user behavior and detecting network anomalies, since there is a need to evaluate big data. The methods and techniques used to detect network anomalies are analyzed. In analyzing the methods and technologies used to detect network anomalies, a classification of anomaly detection methods is proposed. To solve these problems, different algorithms can be used, differing in specificity and, as a result, efficiency. The classification of machine learning methods for detecting network anomalies is considered separately, since machine learning algorithms will be the most effective for the task. Various criteria for evaluating the effectiveness of machine learning models in solving the problem of network traffic profiling are considered. In accordance with the specifics of the tasks of user recognition and network anomaly detection, the most appropriate criteria for evaluating the effectiveness of machine learning models have been selected: AUC ROC the area under the error curve. Four stages of the subsystem for analyzing user behavior and detecting network anomalies are highlighted. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Bionanomaterials in Improving Food Quality and Safety
Current inventions in the area of nanotechnology opened several transformations in scientific and industrial sectors. One such rapidly developing technology gets a lot of application in the food industrys changing the culture of food cultivation to its several branches, like production, processing, packaging, preservation, detection of foodborne pathogens, transportation, shelf life and bioavailability of its valuable nutrients. Far smaller in size and in surface area is strongly related to its stability in terms of chemical and biological activities. Hence, food nanotechnology empowers advancement in several novel bio-nanomaterials with an extensive choice towards potential applications. Nanotechnology benefits the food industry in several ways: to extend and predictable for the growth due to recent and swiftly developing technology influences the characteristic of the food products, which should not get exposed to human and microbial activities. Therefore, implication of bio-nanomaterials in food-related industries pose a significant contribution for economy and also a key community concern. The involvement of nanotechnology throughout the life cycle of food processing, storage, transportation, safety, and potential benefits to mankind are also briefly reviewed in this chapter. Acceptance of nano-based ingredients by the public in various phases of the food business and their associated safety and regulatory measures pertaining to food items can be improved by many methods of nanotechnology. 2025 selection and editorial matter, Shakeel Ahmed; individual chapters, the contributors. -
Blending of Knowledge Management with Industry 4.0: A New Formula for Success!
The convergence of Industry 4.0 and knowledge management presents a transformative opportunity for organizations seeking enhanced efficiency and sustainable growth. In the context of organizational processes, the amalgamation of technological advancements and effective knowledge management practices can lead to a reduction in costs and an overall improvement in operational efficiency. Understanding the intricacies of knowledge management procedures is crucial, encompassing the production, transfer, acquisition, storage, and utilization of knowledge resources across the organizational spectrum. The advent of the fourth industrial revolution, commonly referred to as Industry 4.0, has significantly reshaped traditional knowledge management systems. Industry 4.0 introduces the interconnectivity of machines and their autonomous capacity to learn and share data. While both knowledge management and Industry 4.0 offer distinct benefits individually, a strategic approach that combines the strengths of both can unlock new opportunities for efficient business growth and success in the external environment. This article delves into the symbiotic relationship between Industry 4.0 and knowledge management, emphasizing their combined potential. Industry 4.0 generates vast volumes of data, and by leveraging knowledge management, organizations can derive valuable insights to inform decision-making processes. Historical data and best practices, accessible through knowledge management, contribute to process optimization. Integration with Industry 4.0 technologies, such as automation and the Internet of Things, further enhances process efficiency. The marriage of knowledge management and Industry 4.0 extends beyond process optimization to workforce development. Recognizing employees as the building blocks of an organization, this integration enables better management by upgrading knowledge and skills. Consequently, it enhances the overall productivity of the workforce, contributing to organizational success. In the dynamic landscape of globalization, technology, and competition, this chapter serves as a guide for organizations aiming to harness the collective power of knowledge management and Industry 4.0. By exploring their complementary benefits, it seeks to facilitate the informed utilization of these tools for the betterment and sustainability of businesses in the contemporary world. 2024 Scrivener Publishing LLC. -
Comparative analysis of rural consumers purchase behavior towards mobile phone in Karnataka
Indian urban market is getting saturated for many products. Thus, due to success of brands like Chik shampoo, Project Shakti, LG, Dabur, HLL (then2005), many marketers are now expanding their product offerings to rural markets as well. Also, since major part of India living in villages (around 70%) are now more improved due to increased literacy, TV penetration and improved affordability is a reason for marketers to expand. Of the research conducted on rural India, majority was either on understanding rural consumers on price, quality, brand, function and style or comparing rural consumers over urban consumers on buying behavior. This research focused on comparing rural consumers of two different districts on age, brand and opinion leaders role on influencing the rural preference towards mobile phone. The research focused on understanding the buying behavior of two villages, Keelara and Alekere of Mandya and two villages, Araleri and medahatti of Kolar with reference to mobile phone. 2019 SERSC. -
RIEMANN SOLITONS ON (?,?)-ALMOST COSYMPLECTIC MANIFOLDS
In this paper, we study almost cosymplectic manifolds with nullity distributions admitting Riemann solitons and gradient almost Riemann solitons. First, we consider Riemann soliton on (?,?)-almost cosymplectic manifold M with ? < 0 and we show that the soliton is expanding with (Formula Presented) and M is locally isometric to the Lie group G?. Finally, we prove the non-existence of gradient almost Riemann soliton on a (?,?)-almost cosymplectic manifold of dimension greater than 3 with ? < 0. 2023 Korean Mathematical Society -
IOT based no-parking notifier system
Traffic congestion due to vehicles parked in No-parking zones has become a serious problem in major cities of India. Due to traffic congestion environment, economy and overall quality of life is affected. Hence it is high time to effectively manage the traffic congestion problem. With increase in number of vehicles, discipline in road regulation or traffic system becomes mandatory. The existing traffic system is very accurate but not efficient enough to monitor all the vehicles on the road. With the advent of new technology this problem can be tackled by using Wi-Fi enabled micro-controllers, RFID and cloud systems to monitor every vehicle on the road all the time. This becomes easy for the government in regulating its traffic rules with high efficiency without affecting the smoothness of the traffic. 2018 IEEE. -
Experimental and Analytical Study of High-Strength Concrete Containing Natural Zeolite and Additives
The study compares the durability of Natural Zeolite with Metakaolin, Silica Fume, and Fly Ash on high-strength concrete. 300 concrete specimens were tested for compressive strength before and after an acid attack, modulus of elasticity, water absorption, and rapid chloride permeability. 5%, 10%, and 15% of the cement were replaced with cementitious elements while maintaining the same quantity of Natural Zeolite. In this investigation, the water-cement ratio was maintained at 0.35. After 28 days, the specimens were tested for durability. Samples of all mixes were TG/DT and FTIR tested. The optimal percentages of cementitious materials that resulted to the maximum durability enhancements were reported as the study results. Experimental results showed that Natural Zeolite and Metakaolin strengthened the durability of concrete. All the data show that 5% Natural Zeolite with 10% Metakaolin performs well. Good R2 values and appropriate independent variable coefficients suggested that the regression findings for high-strength concrete durability were accurate. The P values of all models were less than 0.005 and the F values were statistically significant and appropriate; therefore, the generated models predict concrete's strength with authenticity. 2022 by the authors. Licensee C.E.J, Tehran, Iran. -
Experimental and finite element studies on the mechanical properties of high-strength concrete using natural zeolite and additives
Addressing high carbon footprints is a critical global problem in cement production. Using environmentally friendly materials has proven to be a solution to environmental challenges. In this study, High-Strength Concrete of M60 is produced with Natural Zeolite and industrial waste materials. The combinations of 5 % zeolite and varying percentages of industrial wastes such as Silica Fume, Metakaolin, and Fly Ash are tested for mechanical properties. The laboratory test data is compared with numerical simulations to assess the accuracy and determine the error percentage for concrete strength predictions. The process involves the development of numerical solutions by ANSYS to predict strength. The developed numerical solution determines the accuracy of identifying the difference between the experimental and numerical data. The present research on the comparison of experimental and numerical data by ANSYS showed the lowest error percentage, which is acceptable for all the strength properties of concrete. 2024