Volume 9 | Issue 8 |

 Abstract

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Deep Learning, Object Detection, Neural Network, Segmentation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Cyber Security, SQL Query, Attacker, Prevention, Flag, HTML Entities, Vulnerability.

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Creative Commons Attribution 4.0 and The Open Definition

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This project, on account of all the efforts put in, has helped me sharpen my research skills and put my theoretical knowledge to work. After spending a year of MBA program studying different research and marketing techniques, it has been truly a winning experience getting into the field. The project deeply relied on understanding the Hyderabad bakery market and customers, which led me on a course to getting hands on all kinds of information. Further putting my analytics skill acquired during the time, I was able to visualize a statistical view of the culinary customers and market. The project helped me in more than one way. First, it helped me understand the criticality of doing an in-depth market research before opening any new venture and gave me an elevated exposure to the importance of knowing your customer, which is the only way to ensure the success of any business. Through the customer survey, I understood how different customers can be from one another and how their needs vary drastically, leading me to a conclusion that if not of all, businesses should try to tender to the needs of most of their customers. I am hoping to put this information collected to real use and open my own bakery in Hyderabad someday.

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Creative Commons Attribution 4.0 and The Open Definition

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Market Research and Analysis of Bakery Industry in Hyderabad

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract Considering the increased number of vehicles every day, parking supplies should meet parking demands on transportation infrastructure. Irregular construction and excessive population growth in urban areas required re-planning and site selection of parking places. In this study, an analysis was developed to determine location-based parking demand by using Geographic Information System (GIS) techniques. After calculating parking demand and supply balance, the location-allocation techniques of network analysis were implemented to determine the best locations of parking, depending on parking demand. These processing tools were tested for an urban area. As a result, an innovative data processing method was developed to determine the best locations of car parking. Over the years, Geographic Information Systems (GIS) technology has been implemented for a variety of purposes within the transportation industry. With this have come many new uses, benefits, and challenges. This project is able to show the capacity of GIS to support transportation analysis and planning Keywords-component; parking, transportation planning geographic information systems, network analysis.

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parking, transportation planning geographic information systems, network analysis.

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Creative Commons Attribution 4.0 and The Open Definition

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Extract against anti-inflamatory medicine instigated gastric alcer. Mentha Arvensis extract was prepared by using continuous hor extraction (soxhlet) with ethanol.The extract were subjected to preliminary qualitative phytochemical investigation.The plant extract Mentha arvensis drug delivers a diminishing in the ulcer number in the aspirin instigated alcer model in rat.The remedial proportion in the aspirin initiated gastric model was 42%, 54%,72.9%, and 84.12% utilizing ethanolic extricate (100, 250,500 mg/kg), this shows that the plant has antiulcerogenic, antisecretory, and cytoprotective activities. The present data obtained from ethanolic extract of menthe arvensis

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Antiulcerogenic, * Antisecretory, * Cytoprotective activities.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Assessment, Contextual, Barriers, ART, Enrolment, PLHA

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Creative Commons Attribution 4.0 and The Open Definition

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Multimodal neuroimaging analysis offers promising potential for enhancing the diagnosis of Alzheimer's disease and its subtypes. This work proposes an end-to-end framework that integrates structural MRI, synthetically generated PET images, and cognitive test scores to improve diagnostic accuracy and cognitive phenotype characterization. A 2D CycleGAN model is employed to synthesize PET scans from MRI inputs, preserving structural and metabolic consistency, as validated by SSIM and PSNR metrics. The synthesized PET images are labeled using a fine-tuned Inception-based classifier trained on the Kaggle OASIS dataset, achieving a classification accuracy of 98.08%. Patient-level features from both MRI and PET modalities are extracted using ResNet, while cognitive test scores are used to assign phenotypes through a decision tree classifier. Feature-level fusion is then performed to cluster patients into severity-based groups, highlighting the added value of multimodal integration. This framework demonstrates the potential of multimodal pipelines for Alzheimer's diagnosis, providing a foundation for future clinical decision support systems.

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Creative Commons Attribution 4.0 and The Open Definition

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Multimodal fusion, Alzheimer's diagnosis, PET synthesis, CycleGAN, cognitive phenotyping, decision tree, ResNet, Inception, clustering, MRI.

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Supervised machine learning algorithms play a critical role in solving classification problems across science and engineering. This study presents a comparative evaluation of four widely used supervised classification models--Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Decision Tree--using the Iris and Wine benchmark datasets. An experimental design was adopted with an 80/20 stratified train-test split, standard normalization, and label encoding to ensure fair comparison across models. Performance was assessed using accuracy, precision, recall, and F1-score to capture both correctness and robustness of predictions. Results show that SVM consistently achieves the highest accuracy (0.98 for Iris and 0.88 for Wine), followed closely by Logistic Regression, while KNN and Decision Tree generally exhibit lower performance, reflecting sensitivity to feature scaling and over fitting, respectively. These findings confirm that classifier effectiveness strongly depends on dataset characteristics, including separability and feature distributions. The study underscores the necessity of empirical benchmarking when selecting classification algorithms for real-world problems rather than relying on default or heuristic choices. Future research should extend this comparison to ensemble and deep-learning-based classifiers and incorporate larger, higher-dimensional engineering datasets to enhance generalizability

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Creative Commons Attribution 4.0 and The Open Definition

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Supervised machine learning, Classification algorithms, Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbors (KNN)

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Creative Commons Attribution 4.0 and The Open Definition

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Technological advances plus the evolving work and family roles of women in this country have contributed to the business environment of the 21st century. The changing roles of women in India have led to their greater participation in the employment sector and changes in many aspects of Indian life.

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WORKING WOMEN AND THEIR PROBLEMS IN INDIA

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The growing demand for sustainable and energy-efficient cooling solutions in industrial applications has intensified interest in refrigeration systems powered by renewable energy sources. Conventional vapour compression refrigeration systems are heavily dependent on electrical energy derived from fossil fuels, leading to increased operating costs and environmental concerns. In this context, the present work focuses on the design and performance evaluation of a solar-assisted vapour absorption refrigeration system (VARS) intended for industrial cooling applications. The proposed system integrates a solar thermal energy collector with a vapour absorption refrigeration cycle, utilizing low-grade heat energy to drive the refrigeration process. Ammonia-water is considered as the working fluid pair due to its suitability for industrial-scale cooling. The system design parameters, including generator temperature, absorber efficiency, and heat exchanger effectiveness, are analyzed under varying solar radiation conditions. Performance evaluation is carried out in terms of coefficient of performance (COP), cooling capacity, thermal efficiency, and energy savings. The experimental and analytical results demonstrate that solar energy can effectively supplement conventional heat sources, leading to a significant reduction in electrical energy consumption and operational costs. The study confirms that solar-assisted VARS offers a viable, environmentally friendly, and economically attractive alternative for industrial cooling applications, particularly in regions with high solar insolation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Solar-Assisted Refrigeration, Vapour Absorption Refrigeration System, Industrial Cooling, Renewable Energy, Thermal Performance, Coefficient of Performance (COP).

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Creative Commons Attribution 4.0 and The Open Definition