Karnataka State Women's University

Early and accurate diagnosis of diseases in animals is essential for improving veterinary healthcare and reducing mortality. Traditional manual interpretation of X-ray radiographs is often time-consuming and prone to human error, especially in rural veterinary practices. This research presents an automated disease detection framework using Digital Image Processing (DIP) techniques applied to animal X-ray images. The proposed methodology includes image preprocessing, segmentation, feature extraction, and classification using both classical machine learning and deep learning algorithms. Various abnormalities such as bone fractures, lung infections, and soft-tissue irregularities were analyzed. Experimental results demonstrate that deep learning models, particularly Convolutional Neural Networks (CNNs), significantly outperform conventional approaches with improved accuracy and robustness. The study concludes that digital image processing provides an efficient, scalable, and cost-effective diagnostic support system for veterinary medicine.

The sol-gel approach was used to synthesize the copper nanoferrite and magnesium-nickel-silver doped copper nanoferrites in the present work. Several methods were used to characterize the synthesized nanoferrites, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM) and UV-visible spectroscopy. FTIR spectroscopy revealed metal ion peaks at 547-569 cm–1. XRD evaluation indicated that the typical crystallite size was between 20 and 26 nm and the FESEM exhibited non-uniform forms in the synthesized nanoferrites. Elemental analysis revealed the presence of copper, magnesium, nickel and silver in the doped nanoferrites. UV-visible spectroscopy revealed that the direct optical band gap of 1.61 eV for pure copper nanoferrite, 1.53 eV for Cu0.5 and 1.36 eV for Cu0.7. The hysteresis loop of CuFe2O4 nanoparticles was studied to examine their magnetic properties. These findings implies that the synthesized nanoferrites have potential uses in semiconducting device applications and magnetic data storage.

The female characters of Sudha Murthy oeuvre are not only endowed with the name of an elastic resilience, but they are also in fact, a conscious opposition to the cultural hegemony that attempts to restrain them. In my critical analysis, I enlighten on how these women are inverting normative prescriptions in their behavior, actions and heroism. They rebel through the mould of collective expectations by claiming individuality, taste, and fortitude, thus rejecting the domination of the patriarchs, domestic tutelage, injustice in the system and archaic conventions. Their daring act of nonconformity is not a simple vigilante event; it is the act itself, which enables them to create an autonomous story, which puts to pieces any suggestion that they can be nothing more than echoing echoes of others. The paper then questions how the characters of Murthy break their boundaries; how they struggle and triumph in a world dominated by men. By the stories, Murthy challenges the concept of empathy, understanding, and empowerment, and so motivates us to fight in favor of the rights and equality of women. Her writings break the norm and make the reader (at least me) reevaluate the preconceived ideas about the abilities of women in society, thus standing the so-called young, independent women as the sellers of their agency.

Abstract BACKGROUND: The objective of this research was to identify the medicinal plants that are utilized by farmers to treat livestock diseases in Toravi village and Lambadi Thanda of Vijayapura district and evaluate their antioxidant and antibacterial activity against certain bacterial pathogens responsible for gastrointestinal illness in livestock. METHODS: Semi-structured questionnaires were used for data collection. The fidelity level (FL) and informant consensus factor (ICF) were utilized to analyze the collected data. Samples of plant leaves were collected, and the extracts were prepared using distilled water. The agar well diffusion methods were utilized to assess the antibacterial activity of the extracts against pathogenic Staphylococcus aureus , Streptococcus agalactiae , and Escherichia coli . Antioxidant activity was studied by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method. RESULTS: A total of 30 medicinal plants from 18 families with varying habitats, including 11 shrubs, nine trees, nine herbs, and one climber, are utilized in ethnoveterinary practices. Leaves were revealed to be the most commonly utilized component of plants, followed by stem/bark, fruit/seed, root, rhizome, flower, latex, and the entire plant. Fresh ingredients were often favored in medicinal formulas. The results of the ICF indicated a strong consensus for gastrointestinal issues (0.99), mastitis (0.95), respiratory disorder (0.90), fracture (0.89), and dermatological (0.84). Acacia karroo has a high FL value of 100% and is currently being utilized to address gastrointestinal issues in livestock. Preliminary phytochemical screening reveals the presence of phenols, glycosides, alkaloids, terpenoids, tannins, and flavonoids. Maximum inhibition zone was observed in Acacia karroo (6.7 ± 0.08 mm), Cassia auriculata (6.3 ± 0.15 mm), and Tribulus terrestris (6.1 ± 0.12 mm) against S.aureus at 30 mg/mL. DPPH radical scavenging activity of C. auriculata (0.912 ± 0.13%) and A. karroo (0.907 ± 0.15%) was nearer to standard ascorbic acid (1.03 ± 0.65%), followed by T. terrestris (0.871 ± 0.12%), Moringa oleifera (0.719 ± 0.08%), and Vitex negundo (0.642 ± 0.04%) at 100 µg/mL. CONCLUSION: The medicinal plants tested in the Toravi village and Thanda of Vijayapura have been shown to support traditional beliefs regarding their antioxidant and antimicrobial properties in treating bacterial infection. Therefore, further research is recommended to identify and understand the active components present in these plant materials.

Image processing techniques plays important role in animalmedical image or picture to demonstrativeand recognition the disorders and screen the animal(patient) from these infections. The imageprocessing utilizing as a part of numerous applications in the medicinal picture like MagneticResonance Imaging (MRI), Computerized Topography (CT), ultrasound imaging and X-ray imagesetc The x ray or CT or MRI are it may be on fracture of bone , hip joint, vertibrai column ,Nmemonia , Fermur joint, plating, Intenstine and stomach, neck , Lungs, Periodically heart sizecalculating , Fixing rod etc. These images highly exception cost to the diseased animal(patient) when itdo not clear the reimaging is more cost for that, then the picture operation is one of picture preparingstrategies to take care of this issue by less cost and quick. Animal Medicinal pictures are normallycorrupted by commotion amid picture procurement and transmission process. The primary reasonfor the commotion lessening strategy is to remove noise by holding the essential component ofthe pictures. In a run of the mill arrangement of WSN, hubs are battery worked each of thetherapeutic imaging gadgets are influenced by various sorts of commotion. For instance, the x-rayimages are regularly ruined by Poisson commotion, while the ultrasound pictures are influenced bySpeckle noise. Dot is an intricate marvel, which debases picture quality with a back scattered waveappearance which begins from numerous tiny diffused reflections that going through inside organsand makes it more troublesome for the on looker to segregate fine detail of the pictures in analyticexaminations. Accordingly, denoising or lessening this dot commotion from a loud picture hasturned into the dominating stride in medicinal image processing. Magnetic resonance imaging (MRI)of brain is a noninvasive medical imaging technique used in measuring and visualizing the brain’sanatomical structure, analyzing brain abnormalities, delineating pathological regions, surgicalplanning and image guided interventions. X-ray Different image processing techniques are appliedto MRI images for identification, detection and classification of brain diseases as well asabnormalities. In this thesis, we propose an improved classification method, which can detect braintumors and classify as normal and abnormal brain MRI images. The abnormal brain MRI imagesare also classified as Benign and Malignant on the basis of cancerous or non-cancerous state ofbrain tumors. The classification method is developed by using feature extraction process to extractthe features of brain MRI images for detecting the abnormalities and brain tumors. In our proposedmethod, log-polar transformation (LPT) based feature extraction method is constructed to extractthe features from brain MRI images which are performed as detection factor of brain abnormalities.Kernel support vector machine (KSVM) is applied as image classification tools for the tested brainMRI images. Extensive experiments are simulated over different orientation and conversion ofscales in T-1 and T-2 weighted MRI images. A comparative analysis of the proposed method withother existing algorithm is then performed that clarify the significant improvement of the proposed method.