The Intelligent Connection Management Model to Enhance the Security of Cloud Computers in High-Density Fog Networks † Archana Jenis Marianthony Renjitham, Suganthi Subburaj, Ariputhran Durasamy Chandramohan Navin Dhinnesh, Jeyasekaran Jeno Jasmine, Raja Ambethkar Matta Engineering Proceedings, 2023 : The Cloud-Based Secured Connection Management Model (CS-CMM) for high-density fog networks is a novel approach that leverages cloud resources and the proliferation of computing power at the edge of networks. The model seeks to address the challenges encountered when managing large FoNets of numerous devices. The proposed model uses encrypted and secure connections between devices and the cloud infrastructure. This allows for comprehensive and secure management of nodes, devices, and links. The proposed model utilizes shared communication channels to allow for optimal utilization of connectivity resources, and to reduce the latency of communication. The model also utilizes secure protocols for distributed computing and secure communication, ensuring end-to-end security for all nodes. The proposed model employs self-organizing algorithms and adaptive techniques to enable rapid adaptation to changes in network density and topology. This model provides a secure, efficient, and reliable means of managing high-density fog networks.
Semantic based orthographic with prepositional phrase for English-Tamil translation S. Suganthi, P. Bamarukmani, K. G. Srinivasagan, M. Saravanan 4th International Conference on Intelligent Human Computer Interaction Advancing Technology for Humanity Ihci 2012, 2012 Machine translation quality has improved substantially in recent years. Many researchers have contributed and developed quite good algorithms, frameworks and models for various languages. Processing of natural language involves various levels, complexities, ambiguities arise at each of those levels. Some pragmatic and semantic approaches can be used to tackle these issues. Generally, prepositions are plays sound role in meaningful translation for any languages. While translating from English to Tamil, preposition in English sentences should be translated to postposition to have meaningful sentences. Thus the prepositional phase errors and orthographic errors are the major issue in machine translation. The main goal of this paper is to improve the translation quality. To achieve the goal, we use some semantic rule to correct the prepositional and orthographic errors in this English-Tamil translation. The proposed approach takes as input an English sentence containing a preposition and the correct postposition and correct spelling in Tamil for that particular sentence context as output. The rules are evaluated with corpus data and the performance is good. The outcomes of the results are compared with Google Translate.
