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Development of an Adaptive Mathematical Education System for Middle Grades Using Machine Learning
The aim of the study is to improve the study of mathematics topics for middle school children by developing a software implementation of an adaptive educational system using machine learning. During the research, the topic of quadratic equations was chosen as the basis for the research and development of an adaptive system. During the testing of the adaptive system, mistakes were specifically made to simulate the consolidation of knowledge during the educational process and make sure that it works and is able to adapt to the individual level of each student, increasing the level of knowledge gained and contributing to the consolidation of the material. To achieve this goal, Python code was developed in the Jupyter Notebook development environment. Python libraries were also used, in particular the scikit-learn library for implementing machine learning. The presented approach and software implementation can be used both by teachers to check students and track their progress, and by students themselves to assimilate and consolidate the material and knowledge gained in the lessons. The results obtained during the study demonstrate an increase in the effectiveness of adaptive learning methods using machine learning. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Development of an AI Based Framework for Reverse Supply Chain of Pharmaceutical Products
The pharmaceutical reverse supply chain is an integral part of pharmaceutical industry. Due to the complex nature of the process and strict government regulations, it is important to use different AI technologies to increase the efficiency of the reverse supply chain. This research aims to design an AI driven framework for reverse supply chain of pharmaceutical products which would increase efficiency, speed, automate processes and enhance trust among the stakeholders. The framework consists of five modules namely Collection and Sorting Centre, Return Management, Real-time Inventory Management, Disposal Centre, and Data Analytics. In each module different AI technologies have been embedded to increase the efficiency of the system. The proposed framework offers a holistic approach that not only aligns with stringent pharmaceutical standards but also contributes to a more robust, transparent, and environmentally sustainable reverse supply chain. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Development of an Efficient and Secured E-Voting Mobile Application Using Android
Smart technologies, particularly the development of the Internet, are employed to enhance the quality of human existence. Thanks to the Internet's explosive expansion, more and more tasks can now be completed quickly and easily compared to the earlier times. E-voting is a relatively recent field that has been identified. Voting can be conducted in a variety of methods, including in person at a polling place, online, and via a mobile application. The security of applications cannot be disregarded given the internet's explosive growth. In order to prevent phishing attacks, we created an Android application and included a 3-step security process before voting. Students can now vote online from any location at any time using a mobile device. Android Studio is used to create and deploy the application. While creating the voting application, this research adheres to the software development life cycle. The result of this research is the creation of a mobile application that is user-friendly for students and serves as a practical tool for letting them vote with three levels of security. 2022 Anli Sherine et al. -
Development of an efficient real-time H.264/AVC advanced video compression encryption scheme
Multimedia is the combination of media such as text, graphics, video clips, and audio files. In todays world, multimedia plays an important role in many applications that we use in our daily lives. It is used in educational software, animation, sound, and text, as well as multi-media software. H.264/AVC video compression is extremely efficient in terms of compression. Despite this, H.264/AVC requires a lot of processing and consumes a lot of power insdespite of the fact that its compression efficiency is lower than that of H.264/AVC. We examine the various methods of Video H.264 Advanced Video Compression Standard Encryption Schemes in this paper. The performance of all types of encryption techniques will be evaluated using parameters such as cost overhead, delay, and encryption quality. This will provide us with a detailed comparative analysis of video encryption schemes, allowing us to determine which one is far more efficient for H.264/AVC. 2021 Taru Publications. -
Development of an integrated well-being programme for micro, small-and medium-sized enterprise workers in India: A technical note
Workers in Indias micro, small- and medium-sized enterprise (MSME) sector often face a convergence of occupational risks, including long working hours, physical strain, economic insecurity, and limited access to health resources. Despite the sectors critical contribution to national productivity, structured programs addressing the holistic well-being of MSME workers remain scarce. This technical note outlines the development of an integrated well-being intervention designed to enhance physical, psychological, and social health among MSME workers across diverse Indian contexts. Drawing on both indigenous and global practices, the program combines simple yoga-based movements, breathing exercises, and mindfulness techniques with Western approaches such as Jacobsons Progressive Muscular Relaxation (JPMR). The intervention is delivered over two phasesa 21-day facilitator-led group session followed by a 21-day self-practice period to support skill development and habit formation. Designed for scalability and accessibility, the content uses culturally relevant language and experiential activities to ensure engagement in low-literacy and resource-limited settings. This note details the theoretical grounding, content structure, and delivery framework of the program, offering a practical, context-sensitive model that can be adapted for workplace well-being initiatives within the Indian MSME sector. Copyright (c) 2025 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. -
Development of Biocompatible Barium peroxide/Pluronic F127/L-ornithine Composite for Enriched Antimicrobial, Antioxidant and Anticancer Potential: An in vitro Study
Osteosarcoma (MG-63) is a type of bone cancer affects mostly adolescents and young adults. Disease-causing microorganisms like Bacillus subtilis, Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Candida albicans pose serious illness in humans. There is a need to develop multifunctional composite to combat cancer and other most common disease caused by disease causing microorganisms. In this context, BaO2 and pluronic F127, L-Ornithine coated BaO2 (BaO2-PF127-LO) composite have been prepared and characterized by XRD, FTIR, UV-Vis, SEM, HRTEM, EDAX, and XPS analytical techniques. BaO2 and BaO2-PF127-LO were orthorhombic crystalline structure and the crystallite size was found as 32nm for BaO2 and 26nm for modified BaO2 PL studies revealed the green emission observed at 506nm for BaO2-PF127-LO composite which is absent in the case of bare BaO2. Antimicrobial activity of BaO2 and BaO2-PF127-LO was investigated. MTT assay was performed to determine the anticancer potential while the DPPH free radical scavenging assay was carried out to determine the antioxidant potential. The experiment study revealed that the BaO2-PF127-LO exhibited enhanced antimicrobial, antioxidant, and anticancer activity and low toxicity when compared to pristine BaO2. The experimental results revealed that the BaO2-PF127-LO composite holds promising potential for biomedical applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Development of Biocompatible Barium peroxide/Pluronic F127/L-ornithine Composite for Enriched Antimicrobial, Antioxidant and Anticancer Potential: An in vitro Study
Osteosarcoma (MG-63) is a type of bone cancer affects mostly adolescents and young adults. Disease-causing microorganisms like Bacillus subtilis, Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Candida albicans pose serious illness in humans. There is a need to develop multifunctional composite to combat cancer and other most common disease caused by disease causing microorganisms. In this context, BaO2 and pluronic F127, L-Ornithine coated BaO2 (BaO2-PF127-LO) composite have been prepared and characterized by XRD, FTIR, UV-Vis, SEM, HRTEM, EDAX, and XPS analytical techniques. BaO2 and BaO2-PF127-LO were orthorhombic crystalline structure and the crystallite size was found as 32nm for BaO2 and 26nm for modified BaO2 PL studies revealed the green emission observed at 506nm for BaO2-PF127-LO composite which is absent in the case of bare BaO2. Antimicrobial activity of BaO2 and BaO2-PF127-LO was investigated. MTT assay was performed to determine the anticancer potential while the DPPH free radical scavenging assay was carried out to determine the antioxidant potential. The experiment study revealed that the BaO2-PF127-LO exhibited enhanced antimicrobial, antioxidant, and anticancer activity and low toxicity when compared to pristine BaO2. The experimental results revealed that the BaO2-PF127-LO composite holds promising potential for biomedical applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Development of biocompatible NiTi@?-TCP nanocomposite with improved antibacterial and anticancer activities for bone-related biomedical applications
In the present study, ?-TCP and NiTi@?-TCP nanocomposite were synthesized using a modified solgel method. DLS analysis revealed hydrodynamic particle sizes of ?290 nm for ?-TCP and ?231 nm for NiTi@?-TCP, suggesting improved dispersion after NiTi modification. Optical studies showed a red shift in UVVis absorption from 321 nm (?-TCP) to 396 nm (NiTi@?-TCP) with a reduced band gap from 3.8 eV to 3.1 eV, indicating enhanced electronic interactions. Morphological analysis using SEM and HRTEM revealed nanoscale particles (?1530 nm) with clear lattice fringes and polycrystalline diffraction patterns. The NiTi@?-TCP nanocomposite exhibited enhanced antibacterial activity against S. aureus, S. pneumoniae, K. pneumoniae, and Escherichia coli, producing inhibition zones of 17, 13, 14, and 12 mm, respectively, compared with approximately 10 mm for pure ?-TCP. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values for S. aureus were 0.3 mg mL? and 0.5 mg mL? for NiTi@?-TCP, respectively, which were lower than those of ?-TCP (MIC 0.5 mg mL?; MBC 0.7 mg mL?). Histidine scavenger experiments demonstrated that reactive oxygen species (ROS) play a dominant role in bacterial inhibition. Biocompatibility studies using L929 fibroblast cells showed high cell viability (>87% at 150 ?g mL?), confirming good cytocompatibility. In contrast, the nanocomposite exhibited enhanced anticancer activity against MG-63 osteosarcoma cells, with an IC?? value of 115 ?g mL?, compared with 138 ?g mL? for ?-TCP. These results demonstrate that NiTi@?-TCP nanocomposite possesses improved antibacterial and anticancer properties while maintaining good biocompatibility, making it a promising multifunctional biomaterial for biomedical and bone-related therapeutic applications. 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Development of CaO/Chitosan/Dopamine NanoparticlesAntibacterial, Anticancer, andAntioxidant Activities
Infectious diseases and cancer are two significant groups of diseases attributed to the major death around the globe. There is a need to develop innovative strategies to treat antibiotic resistance bacteria and cancer effectively. In this context, the present work focused on development of calcium oxide (CaO) and CaO modified with chitosan and dopamine nanocomposites (CaOCsDop) as potential antibacterial, anticancer, and antioxidant agents. The prepared nanoparticles were characterized using various characterization techniques. FTIR revealed the functional groups of prepared samples indicating the successful preparation of nanoparticles. XRD revealed the fcc cubic nature of CaO nanoparticles and the crystallite size was found to be 23 nm for CaOCsDOP and 31 nm for CaO nanoparticles. DLS results confirmed the mean particle hydrodynamic size was found as nm for 231.90 CaO and 189.90 nm for CaOCsDOP nanocomposite. The disk diffusion assay was carried out against common pathogenic bacterial strains as Pseudomonas aeruginosa, Klebsiella pneumoniae, Vibrio cholerae, Escherichia coli, and Shigella dysenteriae. MTT assay was carried out to determine the anticancer activity against MOLT-4 cell line, a human acute lymphoblastic leukemia model. The results indicated that CaOCsDOP nanocomposites exhibited enhanced antibacterial and anticancer activities compared with bare CaO nanoparticles, making them a promising multifunctional agent in biomedical applications. 2025 Wiley Periodicals LLC. -
Development of carbonaceous anode battery materials from cornstalk and their electrochemical characterization using cyclic voltammetry
This paper presents a study on the development of carbonaceous battery anode material derived from biomass sources, particularly cornstalk for energy storage applications. The carbonization process was optimized, followed by activation and doping with transition metal oxides like nickel and cobalt to enhance the electrochemical performance of the anode material. Cyclic voltammetry and chronopotentiometry studies were employed to characterize the electrochemical properties, specifically the charge storage behavior of the synthesized materials. Fourier transform infrared spectroscopy spectrum, BrunauerEmmettTeller analysis, and scanning electron microscopy were employed to study the impact of doping, surface area, pore size distribution, and surface morphology. The results indicate that doping with metal oxides significantly improves the conductivity and charge storage capacity of the carbon-based materials, making them promising candidates for sustainable battery applications. The Author(s) 2025. -
Development of CeO2ZrO2 bimetallic oxide catalyst for quinoxaline synthesis
In recent years, heterogeneous catalysts have led to environment-friendly transformations with better yields and reusability. Pd, one of the initial metals employed in heterogeneous organic synthesis, suffered from limitations like its high cost. This justifies the need for development of catalysts with abundant, low-cost metals, which has been receiving a lot of attention in the scientific community. In this work, a bimetallic oxide catalyst, CeO2ZrO2, is synthesized by a solgel route. The structure and morphology of the catalyst are investigated using X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray analysis, thermogravimetric analysis, BrunauerEmmettTeller measurements, and temperature-programmed desorption. It is utilized for obtaining quinoxaline derivatives at room temperature. 2,3-Diphenylquinoxaline is obtained via a simple condensation reaction between 1,2-diaminobenzene and 1,2-diketones, catalyzed by CeO2(50)ZrO2(50) with 87% yield in 15 min. Quinoxalines are known for their biological and therapeutic activities; hence, they are essential molecules. The biological activity of the synthesized quinoxaline derivatives has been evaluated against bacterial and fungal strains. 2023 Society of Chemical Industry. 2023 Society of Chemical Industry. -
Development of classical swine fever virus E2-protein based indirect ELISA for detection of antibodies against the virus in pigs
Classical swine fever (CSF) is an economically important and highly contagious disease of pigs caused by CSF virus, genus Pestivirus. Serological diagnosis of the disease is highly valuable for surveillance and thereby containment of spread of the disease. In this study, we have demonstrated the development of CSFV envelope glycoprotein E2-based indirect ELISA (E2-iELISA) for the detection of CSFV specific antibodies. The full-length E2 protein was expressed in E. coli and the purified protein was used as a coating antigen in indirect ELISA for detecting CSFV specific antibodies in pigs. A panel of 506 pig sera samples was used to validate the ELISA and the results were highly comparable to the results obtained with the commercial antibody detection kit (PrioCHECK CSFV Ab kit). The in-house E2-iELISA demonstrated high diagnostic sensitivity (95.4%) and specificity (95.5%), highlighting its potential application for sero-surveillance or monitoring of the disease in the swine population. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Development of effective charging station for EVs using multiport converter and photovoltaic cell integration
The adoption of electric vehicles (EVs) is increasing rapidly as a response to the urgent need to reduce greenhouse gas emissions and dependence on fossil fuels. However, the deployment of a reliable and cost-effective EV charging infrastructure remains a challenge. To address this challenge, this paper proposes the development of an effective charging station using multiport converter and photovoltaic cell integration. A promising approach in the transportation sector is an efficient charging station with multiport converter and photovoltaic cell integration. A multiport converter, photovoltaic cells, a battery energy storage system, and an electric vehicle charging port constitute the proposed charging station. The power flow between the photovoltaic cells, the battery energy storage system, and the electric vehicle charging port is controlled by the multiport converter. The excess energy generated by the photovoltaic cells is stored in the battery energy storage system. The proposed charging station is designed and analysed using MATLAB/Simulink. The simulation results show that the proposed charging station is capable of providing an electric vehicle a reliable and consistent power supply. In contrast to conventional charging stations, the proposed charging station is also capable of offering a faster charging rate. 2024 Nova Science Publishers, Inc. All rights reserved. -
Development of Enhance-Net Deep Learning Approach for Performance Boosting on Medical Images
Only a few clinical procedures include the use of clinical methods for the early detection, observing, evaluation, and treatment evaluation of a range of medical illnesses. Knowing the analysis of medical images in computer vision necessitates being acquainted with the core concepts and uses of deep learning and artificial neural networks. The A rapidly expanding area of study is the Deep Learning Approach (DLA) in medical image processing. DLA is often used in medical imaging to determine if an ailment is present or not. By producing speedier, more accurate results in real time, deep learning algorithms may make the jobs of radiologists and orthopaedic surgeons easier. But the standard deep learning approach has reached its efficiencies. While offering an ideal solution known as boost-Net, we study numerous optimization strategies to increase the effectiveness of deep neural networks in this research. From a selection of well-known deep learning models, Champion-Net was selected as the deep learning model. The musculoskeletal radiograph-bone classification (MURA-BC) dataset is used in this investigation. Utilizing the train and test datasets, Enhance-Net's classification precision was evaluated. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Development of Enhance-Net Deep Learning Approach for Performance Boosting on Medical Images
Only a few clinical procedures include the use of clinical methods for the early detection, observing, evaluation, and treatment evaluation of a range of medical illnesses. Knowing the analysis of medical images in computer vision necessitates being acquainted with the core concepts and uses of deep learning and artificial neural networks. The A rapidly expanding area of study is the Deep Learning Approach (DLA) in medical image processing. DLA is often used in medical imaging to determine if an ailment is present or not. By producing speedier, more accurate results in real time, deep learning algorithms may make the jobs of radiologists and orthopaedic surgeons easier. But the standard deep learning approach has reached its efficiencies. While offering an ideal solution known as boost-Net, we study numerous optimization strategies to increase the effectiveness of deep neural networks in this research. From a selection of well-known deep learning models, Champion-Net was selected as the deep learning model. The musculoskeletal radiograph-bone classification (MURA-BC) dataset is used in this investigation. Utilizing the train and test datasets, Enhance-Net's classification precision was evaluated. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Development of flexible FRP butt joints between stiff FRP panels using hybrid resin and kevlar reinforcement for advanced structural applications
The present work focuses on developing a flexible fiber-reinforced polymer (FRP) butt joint between stiff FRP panels (adherends). The goal is to ensure the joint is flexible, moisture-resistant, and abrasion-resistant, while maintaining the original FRP strength and facilitating the casting of complex and modular shapes. To achieve this, an elastomeric resin system comprising polyurethane and polyurea in an optimized ratio of 10:6 (by weight) was formulated for the flexible joint region, whereas isophthalic polyester resin was used in the stiff FRP panels. The joint was reinforced using a hybrid layup of three layers of plain-weave Kevlar fabric, with glass fiber chopped strand mat (CSM) interleaved between the Kevlar layers, over an overlap length of 50mm on both panel edges. Mechanical characterization revealed that the hybrid resin alone exhibited an average tensile strength of 16.3MPa; however, no slip was observed for the 50mm overlap of the reinforced joint, and failure occurred in the adherend. Furthermore, the joint exhibited favorable performance under abrasion, water immersion, low-temperature fatigue, and drop-weight impact testing. These results confirm that the proposed hybrid Resin-Kevlar reinforced joining approach offers a reliable pathway for fabricating flexible, durable, and high-strength FRP joints suitable for advanced structural applications. The Author(s) 2026. -
Development of Genetic Algorithm Based Neural Network Model for Predicting Strength of High Performance Concrete
Volume 3, Issue -2, ISSN: 2248-9622 -
Development of Genetic Algorithm based Neural Network Model for Predicting Workability and Strength of High Performance Concrete
International Journal of Inventive Engineering and Sciences (IJIES), Vol.2, Issue 6, ISSN : 2319-9598. -
Development of Genetic Algorithm based Neural Network Model For Predicting Workability and strength of High Performance Concrete.
Volume-2 Issue-6, May, ISSN 23199598 -
Development of Green Synthesized Novel Carbon Dots from Ruta Graveolens L. for Fluorescent and Intracellular Sensing of Mercury Ions in Pico-molar (pm) Concentration
Green nanotechnology, which uses carbon nanomaterials for environmental remediation, is the pioneer among the prevailing approaches for the production and characterization. In the present study, highly fluorescent carbon dots (CDs) from Ruta Graveolens (ARH-CD) is developed, and its efficacy as a fluorescent sensor and biomarker is investigated. They act as a fluorescence sensor for Hg2+ over an extensive concentration range of 1 picomolar (pm) to 1 molar (m), with a detection limit as low as 26.75 pm. The studies reveal ARH-CD as an effective biomarker for intracellular toxicity analysis and a fluorescent probe for multi-colored (blue, green, and red) imaging of HEK293 cell lines. After 24 h of incubation, it is found that the ARH material reveals noticeable biocompatibility and visible fluorescence, with a viability of 98.88% at 5 gmL?1 and over 78.33% even at a concentration of 100 gmL?1. The IC50 value for the MTT assay for cell viability results is calculated to be 224.56 4.67 g, which further confirms the appreciable biocompatibility of the ARH-CD. The obtained samples are effective in being inspected for the intracellular detection of Hg2+ and serve as a possible candidate for cell imaging. 2024 Wiley-VCH GmbH.