Any number that can be uniquely determined by a graph is called graph invariants. During the most recent twenty years' innumerable numerical graph invariants have been described and used for correlation analysis. In the fast and advanced environment of manufacturing of networks and other products which used different networks, no dependable assessment has been embraced to choose, how much these invariants are connected with a network graph or molecular graph. In this paper, it will talk about three distinct variations of bridge networks with great capability of expectation in the field of computer science, chemistry, physics, drug industry, informatics, and mathematics in setting with physical and synthetic constructions and networks, since K-Banhatti invariants are newly introduced and have various forecast characteristics for various variations of bridge graphs or networks. The review settled the topology of bridge graph/networks of three unique sorts with three types of K-Banhatti Indices. These concluded outcomes can be utilized for the modeling of interconnection networks of Personal computers (PC), networks like Local area network (LAN), Metropolitan area network (MAN) and Wide area network (WAN), the spine of internet and different networks/designs of PCs, power generation interconnection, bio-informatics and chemical structures.

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The conventional Close circuit television (CCTV) cameras-based surveillance and control systems require human resource supervision. Almost all the criminal activities take place using weapons mostly a handheld gun, revolver, pistol, swords etc. Therefore, automatic weapons detection is a vital requirement now a day. The current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient-Net. Real time datasets, from local surveillance department's test sessions are used for model training and testing. Datasets consist of local environment images and videos from different type and resolution cameras that minimize the idealism. This research also contributes in the making of Efficient-Net that is experimented and results in a positive dimension. The results are also been represented in graphs and in calculations for the representation of results during training and results after training are also shown to represent our research contribution. Efficient-Net algorithm gives better results than existing algorithms. By using Efficient-Net algorithms the accuracy achieved 98.12% when epochs increase as compared to other algorithms.

The Learning management system (LMS) is now being used for uploading educational content in both distance and blended setups. LMS platform has two types of users: the educators who upload the content, and the students who have to access the content. The students, usually rely on text notes or books and video tutorials while their exams are conducted with formal methods. Formal assessments and examination criteria are ineffective with restricted learning space which makes the student tend only to read the educational contents and videos instead of interactive mode. The aim is to design an interactive LMS and examination video-based interface to cater the issues of educators and students. It is designed according to Human-computer interaction (HCI) principles to make the interactive User interface (UI) through User experience (UX). The interactive lectures in the form of annotated videos increase user engagement and improve the self-study context of users involved in LMS. The interface design defines how the design will interact with users and how the interface exchanges information. The findings show that interactive videos for LMS allow the users to have a more personalized learning experience by engaging in the educational content. The result shows a highly personalized learning experience due to the interactive video and quiz within the video.