Computer Engineering Commons^™

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

In Situ Electron Microscopy Of Plasmon-Mediated Nanocrystal Synthesis, Peter Sutter, Ying Li, Christos Argyropoulos, Eli A. Sutter

Department of Electrical and Computer Engineering: Faculty Publications

Chemical processes driven by nonthermal energy (e.g., visible light) are attractive for future approaches to energy conversion, synthesis, photocatalysis, and so forth. The growth of anisotropic metal nanostructures mediated by excitation of a localized surface plasmon resonance (LSPR) is a prototype example of such a reaction. Important aspects, notably the growth mechanism and a possible role of plasmonic “hot spots” within the metal nanostructures, remain poorly understood. Here, we use in situ electron microscopy to stimulate and image the plasmon-mediated growth of triangular Ag nanoprisms in solution. The quantification of the time-dependent evolution of the lateral size and thickness of …

Data Mining Of Protein Databases, Christopher Assi

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Data mining of protein databases poses special challenges because many protein databases are non-relational whereas most data mining and machine learning algorithms assume the input data to be a relational database. Protein databases are non-relational mainly because they often contain set data types. We developed new data mining algorithms that can restructure non-relational protein databases so that they become relational and amenable for various data mining and machine learning tools. We applied the new restructuring algorithms to a pancreatic protein database. After the restructuring, we also applied two classification methods, such as decision tree and SVM classifiers and compared their …