Marcia T Mitchell | Saint Peter's University (original) (raw)

Papers by Marcia T Mitchell

Research paper thumbnail of Mathematical Techniques Used by An English Language Processing Agent Within a Web-Based Parsing System for C++ Instructional Text

Research paper thumbnail of Frontiers in Physiology

Research paper thumbnail of Semantic processing of English sentences using statistical computation based on neurophysiological models

Frontiers in Physiology, 2015

Computer programs that can accurately interpret natural human language and carry out instructions... more Computer programs that can accurately interpret natural human language and carry out instructions would improve the lives of people with language processing deficits and greatly benefit society in general. von Neumann in theorized that the human brain utilizes its own unique statistical neuronal computation to decode language and that this produces specific patterns of neuronal activity. This paper extends von Neumann's theory to the processing of partial semantics of declarative sentences. I developed semantic neuronal network models that emulate key features of cortical language processing and accurately compute partial semantics of English sentences. The method of computation implements the MAYA Semantic Technique, a mathematical technique I previously developed to determine partial semantics of sentences within a natural language processing program. Here I further simplified the technique by grouping repeating patterns into fewer categories. Unlike other natural language programs, my approach computes three partial semantics. The results of this research show that the computation of partial semantics of a sentence uses both feedforward and feedback projection which suggest that the partial semantic presented in this research might be a conscious activity within the human brain.

Research paper thumbnail of MAYA SEMANTIC TECHNIQUE: A Mathematical Technique Used to Determine Partial Semantics for Declarative Sentences

This research uses computational linguistics, an area of study that employs a computer to process... more This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely C++ programming. In this domain all the keywords and programming concepts are known and understood.

Research paper thumbnail of Semantic processing of English sentences using statistical computation based on neurophysiological models

Computer programs that can accurately interpret natural human language and carry out instructions... more Computer programs that can accurately interpret natural human language and carry out instructions
would improve the lives of people with language processing deficits and greatly benefit society in
general. John von Neumann in theorized that the human brain utilizes its own unique statistical
neuronal computation to decode language and that this produces specific patterns of neuronal activity.
This paper extends Von Neumann’s theory to the processing of partial semantics of declarative
sentences. I developed semantic neuronal network models that emulate key features of cortical
language processing and accurately compute partial semantics of English sentences. The method of
computation implements the MAYA Semantic Technique, a mathematical technique I previously
developed to determine partial semantics of sentences within a natural language processing program.
Here I further simplified the technique by grouping repeating patterns into fewer categories. Unlike
other natural language programs, my approach computes three partial semantics. The results of this
research show that the computation of partial semantics of a sentence uses both feedforward and
feedback projection which suggest that the partial semantic presented in this research might be a
conscious activity within the human brain.

Research paper thumbnail of AN ARCHITECTURE OF AN INTELLIGENT TUTORING SYSTEM TO SUPPORT DISTANCE LEARNING

This paper outlines a design framework of an intelligent tutoring system (ITS). ITS focuses on a ... more This paper outlines a design framework of an intelligent tutoring system (ITS). ITS focuses on a newer and more comprehensive distance learning (DL) process as compared to the established traditional DL programs practiced today. The DL model presented in this paper (CHARLIE) is a high level software based tutorial that has the ability to encompass a wide variety of current DL technologies in a single DL session. CHARLIE's architecture has four components: Control Component (responsible for the interaction between software agents and the operating system); Instructional Component (concerned with the instructional aspects of an ITS session); Text Analysis Component (analyzes the partial syntax and partial semantics of the text in the session); Student Modeling Component (analyzes a student's progress and determines the best model for learning during a session). Each component is serviced by a set of software agents to accomplish its mission. Three additional entities in CHARLIE are two separate databases and an explanation facility. Six agents have been implemented in CHARLIE to create a DL course in C++ programming. Much of CHARLIE remains to be completed which opens many areas for research.

Research paper thumbnail of Maya-semantic-technique

This research uses computational linguistics, an area of study that employs a computer to process... more This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely C++ programming. In this domain all the keywords and programming concepts are known and understood.

Research paper thumbnail of Mathematical Techniques Used by An English Language Processing Agent Within a Web-Based Parsing System for C++ Instructional Text

Research paper thumbnail of Frontiers in Physiology

Research paper thumbnail of Semantic processing of English sentences using statistical computation based on neurophysiological models

Frontiers in Physiology, 2015

Computer programs that can accurately interpret natural human language and carry out instructions... more Computer programs that can accurately interpret natural human language and carry out instructions would improve the lives of people with language processing deficits and greatly benefit society in general. von Neumann in theorized that the human brain utilizes its own unique statistical neuronal computation to decode language and that this produces specific patterns of neuronal activity. This paper extends von Neumann's theory to the processing of partial semantics of declarative sentences. I developed semantic neuronal network models that emulate key features of cortical language processing and accurately compute partial semantics of English sentences. The method of computation implements the MAYA Semantic Technique, a mathematical technique I previously developed to determine partial semantics of sentences within a natural language processing program. Here I further simplified the technique by grouping repeating patterns into fewer categories. Unlike other natural language programs, my approach computes three partial semantics. The results of this research show that the computation of partial semantics of a sentence uses both feedforward and feedback projection which suggest that the partial semantic presented in this research might be a conscious activity within the human brain.

Research paper thumbnail of MAYA SEMANTIC TECHNIQUE: A Mathematical Technique Used to Determine Partial Semantics for Declarative Sentences

This research uses computational linguistics, an area of study that employs a computer to process... more This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely C++ programming. In this domain all the keywords and programming concepts are known and understood.

Research paper thumbnail of Semantic processing of English sentences using statistical computation based on neurophysiological models

Computer programs that can accurately interpret natural human language and carry out instructions... more Computer programs that can accurately interpret natural human language and carry out instructions
would improve the lives of people with language processing deficits and greatly benefit society in
general. John von Neumann in theorized that the human brain utilizes its own unique statistical
neuronal computation to decode language and that this produces specific patterns of neuronal activity.
This paper extends Von Neumann’s theory to the processing of partial semantics of declarative
sentences. I developed semantic neuronal network models that emulate key features of cortical
language processing and accurately compute partial semantics of English sentences. The method of
computation implements the MAYA Semantic Technique, a mathematical technique I previously
developed to determine partial semantics of sentences within a natural language processing program.
Here I further simplified the technique by grouping repeating patterns into fewer categories. Unlike
other natural language programs, my approach computes three partial semantics. The results of this
research show that the computation of partial semantics of a sentence uses both feedforward and
feedback projection which suggest that the partial semantic presented in this research might be a
conscious activity within the human brain.

Research paper thumbnail of AN ARCHITECTURE OF AN INTELLIGENT TUTORING SYSTEM TO SUPPORT DISTANCE LEARNING

This paper outlines a design framework of an intelligent tutoring system (ITS). ITS focuses on a ... more This paper outlines a design framework of an intelligent tutoring system (ITS). ITS focuses on a newer and more comprehensive distance learning (DL) process as compared to the established traditional DL programs practiced today. The DL model presented in this paper (CHARLIE) is a high level software based tutorial that has the ability to encompass a wide variety of current DL technologies in a single DL session. CHARLIE's architecture has four components: Control Component (responsible for the interaction between software agents and the operating system); Instructional Component (concerned with the instructional aspects of an ITS session); Text Analysis Component (analyzes the partial syntax and partial semantics of the text in the session); Student Modeling Component (analyzes a student's progress and determines the best model for learning during a session). Each component is serviced by a set of software agents to accomplish its mission. Three additional entities in CHARLIE are two separate databases and an explanation facility. Six agents have been implemented in CHARLIE to create a DL course in C++ programming. Much of CHARLIE remains to be completed which opens many areas for research.

Research paper thumbnail of Maya-semantic-technique

This research uses computational linguistics, an area of study that employs a computer to process... more This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely C++ programming. In this domain all the keywords and programming concepts are known and understood.