A chatbot is a application which is mainly used to provide text-based or text-to-speech online chat
conversations in place of live human chat operators. The chatbot aims to establish connection between and a machine and
a human. The machine incorporates data so that it can recognize the sentences and come to a conclusion in response to an
inquiry. The response principle is the matching of the user's input phrase. The current technological effort involves
establishing a chatbot-based system for college inquiries that uses Natural Language Processing to send natural language
to a server. In this project, we're creating a chatbot that can answer users' questions about the college. The user will be
able to ask the chatbot different questions about the college, including inquiries about the infrastructure and courses. The
user will able to ask various questions to the chatbot about the college, the questions may be concerned with the
infrastructure and courses.
The purpose of this thesis project is to design and implement a vision pipeline useful for self-driving cars, based on computer vision methods and deep learning frameworks. This pipeline is useful for identifying the lane, other cars in the view, as well as traffic signs. A final vision pipeline design is proposed that explores a network that can control steering based on vision input.
Firstly, the working model of computer vision techniques used are presented. The mathematical models used are explored, and implementation in source code developed. These models comprise the vision side of the pipeline.
Secondly, this report explores the deep learning models implemented as part of the pipeline. The mathematical approach is presented as well as the source code implementation. The models are industry and academia proven and their implementation is developed in detail.
The final part provides details on full pipeline architecture, and required hardware. A comprehensive discussion is made on the pipeline, the lessons learned, and future work.
Any electronic walled in area comprises of heat creating electronic components, as heat produced by the electronic parts in a fenced in area decreases the life of electronic segments prompting serious harm or disappointment of the framework. Research shows that each 10°c rise above room temperature of the enclosure, the life of the electronic parts decreases. Thus for any electronic frameworks, cooling turns into a significant structure interest, practical and ideal answer for hold the electronic parts to its working limit. Therefore, in the present work CFD simulation has been carried out using ANSYS Fluent by considering a typical Aluminum Electrical enclosure of volume (150mm X 600mm X 250mm) with total internal heat dissipation of 84W. With those values into consideration the surface area of enclosure, enclosure temperature rise, air flow requirement in an enclosure is calculated and based on which the fan is selected. Also optimization study has been carried out by changing the inlet opening position, exhaust fan location and providing baffle at inlet opening location. The results obtained from analysis are validated with analytical results.
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