Category Archives: Uncategorized

Abstract-Due to the large amount of information generated every day, automatic writing is an important part of knowledge management. The discipline has made great progress, especially with the emergence of abstraction, abstraction and hybrid content models. In the extraction method, the main idea is preserved by selecting the main sentence or phrase from the text, while in the abstraction method, all the information is repeated to create new sentences. As the name suggests, hybrid models include the features of both extraction and abstraction systems to get the best of both approaches. However, issues remain, particularly in how to address the authenticity, coherence, and length of the text. This article examines the current state of writing concepts and topics in practice and future research.

Abstract-The enhancement in web technologies has contributed to the evolution of web applications that are very dynamic and engaging. This research work focuses on the creation of an online image editing application that is based on cloud infrastructure and modern web layouts/development tools such as Next.js, TailwindCSS, and Cloudinary’s APIs, among other resources, to deliver advanced image editing features. The application incorporates Clerk to allow users to create login accounts and easily register, while data is managed using MongoDB to facilitate the security of users and edited pictures across several devices. Necessary and basic features such as object removal, editing backgrounds, recoloring pictures, restoring, and changing the size of images are handled within the cloud and therefore benefit the functionality of the application and users as well. In addition, a contact form utilizing EmailJS has been integrated to enable communication with users. This research work highlights the legitimacy of cloud-based solutions as well as their expanded geographic reach in catering to an advanced user experience within image editing applications, thus supporting the growth of cloud computing and web technology.

Abstract-Diabetes is one of the most frequent diseases worldwide where yet no remedy is discovered for it. Every year a great deal of money has to be spent for caring for patients with diabetes. Therefore, it is crucial that prediction should be very accurate and a very dependable method must be adopted for doing so. One of these methods is the use of artificial intelligence systems, and in particular, the use of Artificial Neural Networks, or ANN. So, in this paper, we used artificial neural networks in order to predict whether or not a person has diabetes. The criterion was to minimize the error function in neural network training with the help of a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 70%

Abstract-This paper examines the pivotal role of mechanical engineering in advancing transportation through innovations like electric vehicles, lightweight materials, and dual-fuel systems. It highlights their impact on sustainability, efficiency, and safety while addressing challenges such as costs, regulations, and public acceptance. Emerging technologies like Hyperloop and hydrogen propulsion are also explored, emphasizing their potential to redefine global mobility.

Abstract-This paper dives into how robotics is transforming manufacturing today. It looks at how robots are making processes faster, safer, and more efficient while also tackling some challenges like high costs and technical complexity. By exploring industries like automotive and consumer goods, and through examples from companies like Toyota and Unilever, the paper highlights both the advantages and limitations of using robots. It also touches on important issues like job impacts and cybersecurity risks, suggesting that thoughtful planning is essential for making the most of robotics in manufacturing.

Abstract-This paper explores the transformative potential of an Augmented Reality (AR) storytelling application designed to enhance traditional storytelling methods by integrating interactive digital animations, text, and audio into physical environments. The app offers a dynamic and immersive experience, particularly for children, by enabling real-time interaction with animated characters, voice narration, and engaging, interactive scenes. Unlike static books or conventional digital content, this app allows users to actively participate in the narrative, creating a more engaging and educational experience. By overlaying digital elements onto the real world, the app fosters increased interactivity and encourages deeper emotional and cognitive engagement with the story. Children can interact with animated characters, explore rich 3D environments, and receive instant feedback through audio cues and animations that respond to their actions. The app also supports educational growth by offering interactive learning modules, promoting reading comprehension, and allowing customization of story elements to accommodate multiple learning styles. The application leverages cutting-edge AR technologies to transform traditional narratives into immersive experiences, providing both entertainment and educational value. By integrating AI-driven components for voice recognition and dynamic content generation, the app can offer personalized experiences and adaptable content based on user preferences and interactions. This survey examines the underlying technologies and design choices that contribute to the app’s ability to engage users, as well as the broader implications of AR in storytelling for enhancing educational tools and creative learning platforms.

Abstract-This paper reviews current research on Alumni Portal, the connections between alumnus and students, college interaction between alumnus, past records, event updates and records. The review covers 30 research papers, investigating database of Alumnus, students, past and present events held, interaction of alumnus in college events, interaction of alumnus and students. For improving the previous Alumni portals and projects related to Alumni.

Abstract-The concept of Shoe Theory emphasizes that everyone is comfortable in their own shoes and should not be forced to wear someone else’s shoes. This theory posits that individual differences, including the effects of various elements such as time and generational perspectives, significantly impact workplace dynamics and organizational effectiveness. The theory highlights the importance of recognizing the unique experiences and backgrounds of team members to foster an inclusive and productive environment. Keeping creative destruction in mind, everything has its loophole to be breached. Although the answer may be yes or no, there always exists a condition of if/situation and but/exception.

Abstract-This paper proposes a flower recognition system using transfer learning with the ResNet-50 architecture. By utilizing pre-trained weights from ResNet-50, the system classifies ten species of flowers, drawing on an extended dataset with over 8,000 labelled images. The study addresses challenges in deep convolutional neural networks, such as overfitting and local optimality, by fine-tuning the ResNet-50 model. Initially, only the final layers of the model are retrained on the flower dataset, while the pre-trained layers remain frozen. After achieving initial convergence, all layers are unfrozen for full model fine-tuning. The dataset is divided into training, validation, and test sets to evaluate the model’s performance, which is measured using accuracy, and F1-score. The experimental results demonstrate that the transfer learning approach significantly improves classification accuracy and generalization, outperforming traditional methods. This approach proves especially effective in handling visually similar flower species and diverse environmental conditions. The study highlights the potential of transfer learning in enhancing the efficiency and robustness of flower recognition systems, contributing to broader applications in image classification tasks.