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Brain Tumor Detectin Using Deep Learning Model
Brain tumor is a life-threatening disease that can disrupt normal brain functioning and have a significant impact on a patient's quality of life. Early detection and diagnosis are crucial for effective treatment. In recent years, deep learning techniques for image analysis and detection have played a vital role in the medical field, supplying more accurate and reliable results. Segmentation, the process of distinguishing between normal and abnormal brain cells or tissues, is a critical step in the detection of brain tumors. In this research, we aim to investigate various techniques for brain tumor detection and segmentation using Magnetic Resonance Imaging (MRI) images. The detection process begins by analyzing the symmetric and asymmetric shape of the brain to identify abnormalities. We will then classify the cells as either Tumored or non-Tumored. This research is aimed at finding a more accurate and efficient method for detecting brain tumors. Four Keras models are compared side by side to find out the best deep learning model for providing a suitable outcome. The models are ResNet50, DenseNet201, Inception V3 and MobileNet. These models gave training accuracy of 85.30%, 78%, 78%, and 77.12% respectively. 2023 IEEE. -
Brain Tumor Classification: A Comparison Study CNN, VGG 16 and ResNet50 Model
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. -
Brain Tumor Classification Using an Ensemble of Deep Learning Techniques
The article reflects on the classification of brain tumors where several deep learning (DL) approaches are used. Both primary and secondary brain tumors reduce the patient's quality of life, and therefore, any sign of the tumor should be treated immediately for adequate response and survival rates. DL, especially in the diagnosis of brain tumors using MRI and CT scans, has applied its abilities to identify excellent patterns. The proposed ensemble framework begins with the image preprocessing of the brain MRI to enhance the quality of images. These images are then utilized to train seven DL models and all of these models recognize the features related to the tumor. There are four models which are General, Glioma, Meningioma, and Pituitary tumors or No Tumor model, which helps in reaching a joint profitable prediction and concentrating solely on the strength of the estimation and outcome. This is a significant improvement over all the individual models, attaining a 99. 43% accuracy. The data used in this research was gotten from Kaggle website and comprised of 7023 images belonging to four classes. Future work will focus on increasing the dataset size, investigating additional DL architectures, and enhancing real-Time detection to improve the accuracy of diagnostic scans and their overall relevance to clinical practice. 2013 IEEE. -
Brain inspired artificial intelligence implant to detect heart disease using reservoir computing /
Patent Number: 202141052156, Applicant: S.Balamurugan.
Research study shows that nearly 30% of the heart attacks occur in patient without any symptoms. Different patterns in medical data could efficiently be identified and classified using Artificial Intelligence Techniques. Research shows that an implant could detect three proteins whose levels are subject to rise after the occurrence of heart attack. Such implants could aid patients with high-risk of heart attack by helping doctors to give appropriate treatment on-time in case of occurrence of heart attack and also to prevent the occurrence of further complications of heart disease. -
Brain image classification using time frequency extraction with histogram intensity similarity
Brain medical image classification is an essential procedure in Computer-Aided Diagnosis (CAD) systems. Conventional methods depend specifically on the local or global features. Several fusion methods have also been developed, most of which are problem-distinct and have shown to be highly favorable in medical images. However, intensity-specific images are not extracted. The recent deep learning methods ensure an efficient means to design an end-to-end model that produces final classification accuracy with brain medical images, compromising normalization. To solve these classification problems, in this paper, Histogram and Time-frequency Differential Deep (HTF-DD) method for medical image classification using Brain Magnetic Resonance Image (MRI) is presented. The construction of the proposed method involves the following steps. First, a deep Convolutional Neural Network (CNN) is trained as a pooled feature mapping in a supervised manner and the result that it obtains are standardized intensified pre-processed features for extraction. Second, a set of time-frequency features are extracted based on time signal and frequency signal of medical images to obtain time-frequency maps. Finally, an efficient model that is based on Differential Deep Learning is designed for obtaining different classes. The proposed model is evaluated using National Biomedical Imaging Archive (NBIA) images and validation of computational time, computational overhead and classification accuracy for varied Brain MRI has been done. 2022 CRL Publishing. All rights reserved. -
Brahma Nirupan of Kabir: A Search for Ultimate Reality
Kabir Das was a fifteenth-century Indian mystic. Saint Kabir's philosophical tenets were extremely simple. He was known as the guiding spirit of the Bhakti movement. According to Kabir, Braham Nirupan is the ultimate reality called Ni-Akshar, which is only possible through Sar Shabda. Charlotte Vaudeville stated in her book named Kabir that Kabir is a weaver, the best-known and the most revered name in Indian tradition(Vaudeville, 1993). By performing service with full loving devotion, one can achieve Sar Shabda and become a Hansa. The liberated soul is blessed and can enjoy the pleasurable experience of Sar Shabda. The iconoclastic Saint Kabir is a symbol of the syncretic culture of India. Kabir refused to say if he was a Hindu or a Muslim. In today's polarized culture, Kabir's vision and love are desperately needed. Caste and religious divisions have exacerbated the fault line in our society. This paper focuses on the concept of Brahma Nirupan and the philosophy of Kabir Das and how in this materialistic world one can seek the ultimate truth while being a part of this world yet not being attached to it. Indian Council of Philosophical Research 2025. -
Bracing up for financial inclusivity: the CabDost way
Learning outcomes: The learning outcomes of this study are as follows: 1. understand the role of financial inclusivity in the sustainable development of a nation; 2. examine the concept of social entrepreneurship and identify the skills needed to be a social entrepreneur; 3. analyze the opportunities and challenges faced by social entrepreneurs, especially in an emerging economy; and 4. assess the feasible options with respect to upscaling and expansion. Case overview/synopsis: Yamuna Sastry, a young woman from a traditional Indian family, had set out to achieve her dream of financial inclusivity by helping the underprivileged in her country gain financial independence and credibility. When she was approached by a cab driver to file tax returns for him, a new venture took shape in her mind, and along with a partner, CabDost, a socially driven financial advisory start-up was created to provide financial advisory services exclusively for cab drivers. CabDost had been instrumental in making over 15,000 cab drivers financially literate, instilling in them a culture of compliance, getting them tax refunds and enabling the Indian Government recover eight crores in taxes. The success of financial inclusivity among cab drivers inspired CabDost to extend its financial services to truck drivers, auto drivers, housekeeping staff and other contractual workforce. The company found it challenging to address the demands of the increasing customer base with its available technical resources. The absence of an in-house tech team and the need for an all-in-one tech platform to provide a wide variety of financial services induced CabDost to explore other options. Dvara Money, a neo bank offering financial services, approached CabDost with a merger proposal. Though it was a lucrative offer, the founding members were apprehensive as they knew that most of the mergers failed because of myriad reasons. They were contemplating on their next move as they were in a dilemma about whether to develop a technical team in-house or to go ahead with the merger. Complexity academic level: The case can be taught to business management students as a part of the introductory course on entrepreneurship or social entrepreneurship. The case can be used specifically to make the students understand the role of financial inclusivity in the sustainable development of a nation, the concept of social entrepreneurship, the journey of social entrepreneurs in the financial inclusivity space, right from ideation to execution, the challenges faced in the bargain, survival mechanisms adopted and the various options available for further growth and expansion. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 3: Entrepreneurship. 2023, Emerald Publishing Limited. -
BoxBehnken design and experimental study of ciprofloxacin degradation over Ag2O/CeO2/g-C3N4 nanocomposites
Abstract: The presence of pharmaceutical residues notably antibiotics in the environment is an increasing concern due to their persistence and toxicity. Developing efficient and eco-friendly methods to eliminate antibiotic residues from water bodies has become a major environmental challenge. CeO2 doped with a heteroatom forms a hybrid structure with g-C3N4 and could serve as an efficient photocatalytic agent. In this study, CeO2/g-C3N4 and Ag2O/CeO2/g-C3N4 hybrid catalysts were prepared for UV light degradation of ciprofloxacin (CIP) antibiotic. The various factors that influence the degradation were experimentally optimized. The kinetics of the degradation was investigated using the LangmuirHinshelwood kinetic model. The effect of three operational parameters influencing the photocatalytic degradation has been evaluated using BoxBehnken design of response surface methodology. The highest degradation of CIP was observed at CIP concentration of 10?g/L with a catalyst amount of 30mg after 2.5h. Efficient charge separation was achieved from the dopant and the existing integrated electric field of the heterojunction showed impressive higher activity. Graphic abstract: [Figure not available: see fulltext.]. 2020, Islamic Azad University (IAU). -
Bounds related to product variants of graphs
Operations in graph theory have a significant influence in the theoretical and application aspect of the domain. Topological indices serve as a crucial component in chemical graph theory linked with some molecular structure. Recently, the study on the new graph product variants is initiated. In the article, the computation of some bounds for atom-bond connectivity index, inverse sum indeg index, geometric-arithmetic index and sombor index of graph operations notably the corona join product, subdivision vertex join product and the subdivision vertex-edge join is carried out. Palestine Polytechnic University-PPU 2023. -
Bounds on Sombor index of graph operations
Operations in graph theory have a significant influence in the theoretical and application aspect of the domain. Topological indices serve as a crucial component in chemical graph theory linked with some molecular structure. Recently, Gutman initiated the study on the Sombor index. In this paper, the computation of some bounds for Sombor index of graph operation notably join, cartesian product, corona product, lexicographic product, tensor product and strong product is carried out. The computation has been utilized to determine the upper bounds of the index for the specified graph operations for some standard graphs like the path and cycle graphs. 2025 World Scientific Publishing Company. -
Bounds on Sombor index of graph operations
Operations in graph theory have a significant influence in the theoretical and application aspect of the domain. Topological indices serve as a crucial component in chemical graph theory linked with some molecular structure. Recently, Gutman initiated the study on the Sombor index. In this paper, the computation of some bounds for Sombor index of graph operation notably join, cartesian product, corona product, lexicographic product, tensor product and strong product is carried out. The computation has been utilized to determine the upper bounds of the index for the specified graph operations for some standard graphs like the path and cycle graphs. 2025 World Scientific Publishing Company. -
Bounds on Sombor Index for Corona Products on R-Graphs
Operations in the theory of graphs has a substantial influence in the analytical and factual dimensions of the domain. In the realm of chemical graph theory, topological descriptor serves as a comprehensive graph invariant linked with a specific molecular structure. The study on the Sombor index is initiated recently by Ivan Gutman. The triangle parallel graph comprises of the edges of subdivision graph along with the edges of the original graph. In this paper, we make use of combinatorial inequalities related with the vertices, edges and the neighborhood concepts as well as the other topological descriptors in the computations for the determination of bounds of Sombor index for certain corona products involving the triangle parallel graph. 2024 Azarbaijan Shahid Madani University. -
Bounds of Sombor Index for F-Sum Operation
Graph operations have a major impact in the aspects of theory and empirical literature of the domain. For relating the molecular topology to any real chemical attribute, the conversion of the relevant details embedded into chemical structure to some numeric value becomes so vital which ultimately paves the way for the emergence of topological indices. Topological descriptor acts as an effective graph invariant in chemical graph theory associated with certain molecular structure. Recently, the study on the sombor index is initiated by I.Gutman [16]. In the article, we utilise combinatorial inequalities, including the general sum-connectivity index, the first general zagreb index and few other indices in their formulations, for the determination of bounds for sombor index for the F-sum operation of connected graphs. Palestine Polytechnic University-PPU 2023. -
Bounds for Zagreb class of indices on alkylating agents
The family of Zagreb indices have a pivotal role in predicting various physiochemical properties of molecules. Alkylating agents are some of the main classes of anticancer drugs. In this paper we find the bounds of some Zagreb indices. 2022 Author(s). -
Boundary layer flow of magneto-nanomicropolar liquid over an exponentially elongated porous plate with Joule heating and viscous heating: a numerical study
Micropolar fluids are used in lubrication theory, thrust bearing technologies, cervical flows, lubricants, paint rheology, and the polymer industry. This study develops the numerical simulation of the magneto-Darcy flow of a polarized nanoliquid with Joule heating and viscous heating mechanisms on an exponentially elongated surface. The effects of linearized Rosseland radiation and temperature-dependent heat generation are considered. The flow is generated by an exponential form of elongation of a flexible sheet. The porous matrix and nanoparticle effects are characterized by the Darcy expression and the two-component Buongiorno model correspondingly. The resulting partial differential systems are solved numerically using the RungeKutta-based shooting technique to interpret the importance of key parameters in physical quantities. A direct comparison is made to validate the results. Our results demonstrated that arbitrary movement of the nanoparticles significantly advances the temperature profile by reducing the concentration of nanoparticles. Both Joule heating and viscous heating mechanisms improve the structure of the thermal boundary layer. The porous matrix reduces the velocity of the nanoliquid and thus the width of the velocity boundary layer is reduced. 2021, King Fahd University of Petroleum & Minerals. -
Bougainvillea glabra-mediated synthesis of Zr?O and chitosan-coated zirconium oxide nanoparticles: Multifunctional antibacterial and anticancer agents with enhanced biocompatibility
The effectiveness and safety of nanomaterials (NMs) are essential for their use in healthcare. This study focuses on creating NPs with multifunctional antibacterial and anticancer properties to combat bacterial infections and cancer disease more effectively than traditional antibiotics. This study investigates the synthesis of Zr3O and chitosan (ch) coated zirconium oxide nanoparticles (chZrO NPs) using Bougainvillea glabra (B. glabra) plant extract through a green, one-pot precipitation method. The synthesized NPs were analyzed using various techniques. Their antibacterial properties are attributed to the production of reactive oxygen species (ROS), influenced by their size, large surface area, oxygen vacancies, ion release, and diffusion capabilities. The chZrO NPs showed superior antibacterial activity compared to Zr3O and chitosan alone, with effective inhibition against both Gram-positive bacteria (S. aureus and B. subtilis) and Gram-negative bacteria (E. coli and P. aeruginosa). Additionally, anticancer studies of chZrO NPs demonstrated significant activity against colon cancer HCT116 cells with C50 values of 4.98 ?g/mL compared to chitosan and Zr3O with 9.62, 6.69 ?g/mL, while biocompatibility tests on L929 cells confirmed their safety showing 93 % cell viability compared to ch and Zr3O. These findings suggest that chZrO NPs are promising candidates for future use in clinical and healthcare applications. 2025 Elsevier B.V. -
Bougainvillea glabra-mediated synthesis of Zr?O and chitosan-coated zirconium oxide nanoparticles: Multifunctional antibacterial and anticancer agents with enhanced biocompatibility
The effectiveness and safety of nanomaterials (NMs) are essential for their use in healthcare. This study focuses on creating NPs with multifunctional antibacterial and anticancer properties to combat bacterial infections and cancer disease more effectively than traditional antibiotics. This study investigates the synthesis of Zr3O and chitosan (ch) coated zirconium oxide nanoparticles (chZrO NPs) using Bougainvillea glabra (B. glabra) plant extract through a green, one-pot precipitation method. The synthesized NPs were analyzed using various techniques. Their antibacterial properties are attributed to the production of reactive oxygen species (ROS), influenced by their size, large surface area, oxygen vacancies, ion release, and diffusion capabilities. The chZrO NPs showed superior antibacterial activity compared to Zr3O and chitosan alone, with effective inhibition against both Gram-positive bacteria (S. aureus and B. subtilis) and Gram-negative bacteria (E. coli and P. aeruginosa). Additionally, anticancer studies of chZrO NPs demonstrated significant activity against colon cancer HCT116 cells with C50 values of 4.98 ?g/mL compared to chitosan and Zr3O with 9.62, 6.69 ?g/mL, while biocompatibility tests on L929 cells confirmed their safety showing 93 % cell viability compared to ch and Zr3O. These findings suggest that chZrO NPs are promising candidates for future use in clinical and healthcare applications. 2025 Elsevier B.V. -
Boron-/nitrogen-doped Ti3C2Tx MXene quantum dot-based sensor for determining an acute kidney injury biomarker
In this study, boron/nitrogen-doped Ti3C2Tx MXene quantum dots (BNMQDs) were synthesized via a hydrothermal technique and successfully brush-coated on a carbon fiber paper (CFP)-based electrode to detect creatinine (crt). The prepared MQDs were characterized by employing transmission electron microscopy (TEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), infrared spectroscopy (IR), and X-ray diffraction (XRD) analysis to study their physicochemical properties. The electrochemical performance of the modified CFP-based sensors toward crt detection was analyzed by employing cyclic voltammetry (CV) and differential pulse voltammetry (DPV). Ti3C2Tx MQDs were prepared using the hydrothermal method and further doped with B and N using boric acid and p-phenylene diamine, respectively. The morphology of the obtained BNMQDs was quasi-spherical and exhibited uniform size with scattered particle sizes ranging from 5 to 9.5 nanometers. Owing to several surface-active sites, edge effects, and quantum confinement, the synthesized MQDs demonstrated enhanced electrooxidation of crt. Compared to BMQDs and NMQDs, BNMQDs showed superior sensing performance, with a wide linear range of 0.104-135 ?M and an LOD of 34.53 nM. The fabricated electrode also demonstrated high stability, reproducibility, and selectivity for the electrocatalytic oxidation of crt in real samples. 2025 The Royal Society of Chemistry. -
Borne dreamily along the River of Stories: polyphony, anthropoharmonism and the search for indigenous epistemologies in Orijit Sens graphic novel
This paper offers a close reading and analysis of Orijit Sens The River of Stories (1994), often hailed as the first Indian graphic novel. Based on the historical events of the 1990s, Sens work revolves around the Narmada Bachao Andolan, a milestone movement in the annals of Indian environmentalism that resisted the construction of dams across the Narmada River. This project led to the displacement of the tribal population residing along the river bank and destroyed their livelihood. The paper employs Bakhtins concept of polyphony to explore the richly layered nature of Sens graphic novel. The graphic novel calls upon its readers to constantly navigate the diverse, often conflicting perspectives offered by different characters as well as the complex interplay between words and images. Drawing upon the works of posthumanist philosophers like Braidotti, Hathaway and Scharper, the paper argues that, through characters like Malgu gayan, The River of Stories presents a passing vision of anthropoharmonism, i.e. harmony between mankind and the natural world. However, the overarching presence of the influential and corrupt State officials, blindly seeking progress and development underscores that it is only through the relentless quest to uncover and preserve indigenous epistemologies, comprising lost tribal cultures and folk traditions, that this harmonious vision can be realised. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Borders and Control: Negotiating Mobility, Security, and Rights in Digital Regimes
Despite millions crossing the border, the right of mobility has been restricted in lieu of states' discretion based on their sovereignty. This brings the authors to the age-old debate on mobility and border control. Amidst the tussle between the human right of mobility and the sovereign right of nation-states, the role of technology continues to influence the security lens of nation-states' borders. Recently, the EU, USA, Canada, Australia and other host countries installed digital border measures. A cross jurisdictional study of the above mentioned four jurisdictions highlight the surveillance and information-sharing system deployed at borders. The aim of the chapter is to assess the systemic efficiency of Digital Border Governance in Global North and South as means of securitization. Digital border governance brings an inevitable risk of abuse of data obtained at borders which can be remedied only via means of an inclusive regime built on the three pillars of fairness, transparency, and cooperation. 2026 by IGI Global Scientific Publishing. All rights reserved.