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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 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 Strength of High Performance Concrete
Volume 3, Issue -2, ISSN: 2248-9622 -
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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. -
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Development of Family Intervention for Management of Psychogenic Seizures : A Qualitative Study
Background: In the somatoform and dissociative spectrum, family functioning has been poorly researched based on the search in PubMed, Google Scholar, Science Direct, PROQUEST, EBSCO and Cochrane Reviews. In Psychogenic Non-Epileptic Seizures (PNES) primarily, family functioning has been understood as a comparison between Epileptic Seizures (ES) and PNES. However, an attempt to study different aspects of family functioning and its ability to influence the newlinemanifestation of the disorder is yet to be made. Methods: This study attempted to understand different family functions qualitatively by interviewing both the patients and family members of these patients. Nine patients and seven families of these patients participated in the study. Braun and Clarke s thematic model was used. Latent thematic analysis was used to analyse the data. Based on the analysis, major and sub-themes were used to develop family intervention and a family psychoeducational model. Both were developed with the help of the GUIDED Checklist to report health interventions; the TIDieR format and Delphi newlinetechnique was used to collect the expert opinion of the developed intervention. newlineResults: Two sets of results and analyses were compiled with qualitative data, that is, for patients and families. Major themes and sub-themes were developed for both, including family interaction, attachment, poor communication, structural-systemic aspects, distressful family aspects, negative newlineexpressed emotions, cultural aspects, nature of the illness, family s views of the illness and coping mechanisms. These themes indicated the importance of family functioning and its impact on the manifestation of the disorder. newlineConclusion: The researcher concludes that family dysfunction can impact the manifestation of the disorder. Hence, an additional family intervention or psychoeducation is essential for holistic newlinetreatment. -
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 empirical formulas to determine the shear planes /
Patent Number: 202141033078, Applicant: Nanjunda K N.
The determination of shear planes is very essential in order to determine the design capacity of bolted joint due to single shear force or double shear force acted in either in lap joint or but joint. The shear plane is the plane between two or more pieces under the load where the pieces tend to move parallel from each other, but in opposite directions. The shear planes for lap joint and but joint with double cover plates with numbers of bolts are analysed. From this result empirical formulas are developed. -
Development of efficient biometric recognition algorithms based on fingerprint and face /
The reliable verification systems are required to verify and confirm the identity of an individual requesting their service. Secure access to the buildings, laptops, cellular phones, ATM etc. is an example of such applications. In the absence of robust verification systems, these systems are vulnerable to the wiles of an impostor. The traditional ways of authentications are passwords (knowledge ?? based security) and the ID Cards (token ?? based security). These methods can be easily breached due to the chance of stolen, lost or forget. The development and progress of biometrics technology, the fear of stolen, lost or forget can be eliminated. Biometrics refers to the automatic identification (or verification) of an individual (or a claimed identity) by using certain physiological or behavioral traits associated with the person. The biometrics identifies the person based on features vector derived from physiological or behavioural characteristics such as uniqueness, permanence, accessibility, collectability with minimum cost. The physiological biometrics are Fingerprint, Hand Scan, Iris Scan, Facial Scan and Retina Scan etc., and behavioural biometric are Voice, Keystroke, Gait, Signature etc., The physiological biometrics measures the specific part of the structure or shape of a portion of a subjects body. But the behavioural biometric are more concerned with mood and environment. Chapter one presents the introduction to biometrics and its various traits. Further description like structure of the biometric system, different approaches are discussed. Also the design issues in biometric system such as universality, collectability, distinctiveness, permanence, acceptability, uniqueness, performance, circumvention etc., are discussed. Chapter two gives a detailed survey of biometric techniques. It includes the literature survey of fingerprint and face biometric traits and various approaches. In Chapter three, the algorithm of Fingerprint Verification based on Dual Tree Complex Wavelet Transformation (DTCWT) is proposed. The original fingerprint is cropped and resized to apply the DTCWT. The features of Fingerprint are obtained by applying different levels of DTCWT. Performance analysis is discussed with the FRR, FAR and TSR. Chapter four discusses another highly recommended source of authentication such as face recognition. In this chapter, the algorithm of Performance Comparison of Face Recognition using Transform Domain Techniques (PCFTD) is proposed. The face databases L ?? Spacek, JAFFE and NIR are considered. The features of face are generated using wavelet families such as Haar, Symelt and DB1 by considering approximation band only. The face features are also generated using magnitudes of FFTs. The test image features are compared with database features using Euclidian Distance (ED). The performance parameters such as FAR, FRR, TSR and EER computed using wavelet families and FFT. The methodology described in this paper is accurate, simple, fast and better than the existing algorithms. Chapter five presents conclusion and future work. -
Development of Efficient Biometric Recognition algorithms based on Fingerprint and Face
The reliable verification systems are required to verify and confirm the identity of an individual requesting their service. Secure access to the buildings, laptops, cellular phones, ATM etc. is an example of such applications. In the absence of robust verification systems, these systems are vulnerable to the wiles of an impostor. The traditional ways of authentications are passwords (knowledge based security) and the ID Cards (token based security). These methods can be easily breached due to the chance of stolen, lost or forget. The development and progress of biometrics technology, the fear of stolen, lost or forget can be eliminated. Biometrics refers to the automatic identification (or verification) of an individual (or a claimed identity) by using certain physiological or newlinebehavioral traits associated with the person. newlineThe biometrics identifies the person based on features vector derived from physiological or behavioural characteristics such as uniqueness, permanence, accessibility, collectability with minimum cost. The newlinephysiological biometrics are Fingerprint, Hand Scan, Iris Scan, Facial Scan and Retina Scan etc., and behavioural biometric are Voice, Keystroke, Gait, Signature etc., The physiological biometrics measures the specific part of the structure or shape of a portion of a subject s body. But the behavioural biometric are more concerned with mood and environment.Chapter one presents the introduction to biometrics and its various newlinetraits. Further description like structure of the biometric system, different newlineapproaches are discussed. Also the design issues in biometric system such as universality, collectability, distinctiveness, permanence, acceptability, newlineuniqueness, performance, circumvention etc., are discussed. Chapter two gives a detailed survey of biometric techniques. It includes the literature survey of fingerprint and face biometric traits and various approaches. -
Development of efficient biometric recognition algorithms based on fingerprint and face
The reliable verification systems are required to verify and confirm the identity of an individual requesting their service. Secure access to the buildings, laptops, cellular phones, ATM etc. is an example of such applications. In the absence of robust verification systems, these systems are vulnerable to the wiles of an impostor. The traditional ways of authentications are passwords (knowledge – based security) and the ID Cards (token – based security). These methods can be easily breached due to the chance of stolen, lost or forget. The development and progress of biometrics technology, the fear of stolen, lost or forget can be eliminated. Biometrics refers to the automatic identification (or verification) of an individual (or a claimed identity) by using certain physiological or behavioral traits associated with the person. The biometrics identifies the person based on features vector derived from physiological or behavioural characteristics such as uniqueness, permanence, accessibility, collectability with minimum cost. The physiological biometrics are Fingerprint, Hand Scan, Iris Scan, Facial
Scan and Retina Scan etc., and behavioural biometric are Voice, Keystroke, Gait, Signature etc., The physiological biometrics measures the specific part of the structure or shape of a portion of a subject’s body. -
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 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 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 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 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 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 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.