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Full-Text Articles in Physical Sciences and Mathematics
A Novel Handover Method Using Destination Prediction In 5g-V2x Networks, Pooja Shyamsundar
A Novel Handover Method Using Destination Prediction In 5g-V2x Networks, Pooja Shyamsundar
Master's Projects
This paper proposes a novel approach to handover optimization in fifth generation vehicular networks. A key principle in designing fifth generation vehicular network technology is continuous connectivity. This makes it important to ensure that there are no gaps in communication for mobile user equipment. Handovers can cause disruption in connectivity as the process involves switching from one base station to another. Issues in the handover process include poor load management for moving traffic resulting in low bandwidth or connectivity gaps, too many hops resulting in multiple unneccessary handovers, short dwell times and ineffective base station selection resulting in delays and …
Caption And Image Based Next-Word Auto-Completion, Meet Patel
Caption And Image Based Next-Word Auto-Completion, Meet Patel
Master's Projects
With the increasing number of options or choices in terms of entities like products, movies, songs, etc. which are now available to users, they try to save time by looking for an application or system that provides automatic recommendations. Recommender systems are automated computing processes that leverage concepts of Machine Learning, Data Mining and Artificial Intelligence towards generating product recommendations based on a user’s preferences. These systems have given a significant boost to businesses across multiple segments as a result of reduced human intervention. One similar aspect of this is content writing. It would save users a lot of time …
Graph Neural Networks For Malware Classification, Vrinda Malhotra
Graph Neural Networks For Malware Classification, Vrinda Malhotra
Master's Projects
Malware is a growing threat to the digital world. The first step to managing this threat is malware detection and classification. While traditional techniques rely on static or dynamic analysis of malware, the generation of these features requires expert knowledge. Function call graphs (FCGs) consist of program functions as their nodes and their interprocedural calls as their edges, providing a wealth of knowledge that can be utilized to classify malware without feature extraction that requires experts. This project treats malware classification as a graph classification problem, setting node features using the Local Degree Profile (LDP) model and using different graph …