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Articles 241 - 248 of 248
Full-Text Articles in Artificial Intelligence and Robotics
Using Neural Networks For Image Classification, Tim Kang
Using Neural Networks For Image Classification, Tim Kang
Master's Projects
This paper will focus on applying neural network machine learning methods to images for the purpose of automatic detection and classification. The main advantage of using neural network methods in this project is its adeptness at fitting nonlinear data and its ability to work as an unsupervised algorithm. The algorithms will be run on common, publically available datasets, namely the MNIST and CIFAR10, so that our results will be easily reproducible.
Using Probabilistic Graphical Models To Solve Np-Complete Puzzle Problems, Fengjiao Wu
Using Probabilistic Graphical Models To Solve Np-Complete Puzzle Problems, Fengjiao Wu
Master's Projects
Probabilistic Graphical Models (PGMs) are commonly used in machine learning to solve problems stemming from medicine, meteorology, speech recognition, image processing, intelligent tutoring, gambling, games, and biology. PGMs are applicable for both directed graph and undirected graph. In this work, I focus on the undirected graphical model. The objective of this work is to study how PGMs can be applied to find solutions to two puzzle problems, sudoku and jigsaw puzzles. First, both puzzle problems are represented as undirected graphs, and then I map the relations of nodes to PGMs and Belief Propagation (BP). This work represents the puzzle grid …
Comparative Analysis Of Particle Swarm Optimization Algorithms For Text Feature Selection, Shuang Wu
Comparative Analysis Of Particle Swarm Optimization Algorithms For Text Feature Selection, Shuang Wu
Master's Projects
With the rapid growth of Internet, more and more natural language text documents are available in electronic format, making automated text categorization a must in most fields. Due to the high dimensionality of text categorization tasks, feature selection is needed before executing document classification. There are basically two kinds of feature selection approaches: the filter approach and the wrapper approach. For the wrapper approach, a search algorithm for feature subsets and an evaluation algorithm for assessing the fitness of the selected feature subset are required. In this work, I focus on the comparison between two wrapper approaches. These two approaches …
Using Hidden Markov Models To Detect Dna Motifs, Santrupti Nerli
Using Hidden Markov Models To Detect Dna Motifs, Santrupti Nerli
Master's Projects
During the process of gene expression in eukaryotes, mRNA splicing is one of the key processes carried out by a complex called spliceosome. Spliceosome guarantees proper removal of introns and joining of exons before the translation process. Precise splicing is essential for the production of functional proteins. Spliceosome detects specific sequence motifs within an mRNA sequence called splice sites. Two of the splice sites are the 5’ and 3’ sites that border all the introns. Normal splicing process if disrupted by mutation may lead to fatal diseases. In this work, we predict splice sites in a human genome using hidden …
Financial Ratio Analysis For Stock Price Movement Prediction Using Hybrid Clustering, Tom Tupe
Financial Ratio Analysis For Stock Price Movement Prediction Using Hybrid Clustering, Tom Tupe
Master's Projects
We have gathered over 3100 annual financial reports for 500 companies listed on the S&P 500 index, where the main goal was to select and give proper weights to the various pieces of quantitative data to maximize clustering results and improve prediction results over previous work by [Lin et al. 2011]. Various financial ratios, including earnings per share surprise percentages were gathered and analyzed. We proposed and used two types, correlation based ratios and causality based ratios. An extension to the classification scheme used by [Lin et al. 2011] was proposed to more accurately classify financial reports, together with a …
Masquerade Detection Using Singular Value Decomposition, Sweta Vikram Shah
Masquerade Detection Using Singular Value Decomposition, Sweta Vikram Shah
Master's Projects
Information systems and networks are highly susceptible to attacks in the form of intrusions. One such attack is by the masqueraders who impersonate legitimate users. Masqueraders can be detected in anomaly based intrusion detection by identifying the abnormalities in user behavior. This user behavior is logged in log files of different types. In our research we use the score based technique of Singular Value Decomposition to address the problem of masquerade detection on a unix based system. We have data collected in the form of sequential unix commands ran by 50 users. SVD is a linear algebraic technique, which has …
Learning Author’S Writing Pattern System By Automata, Qun Yu
Learning Author’S Writing Pattern System By Automata, Qun Yu
Master's Projects
The purpose of the report is to document our project’s theory, implementation and test results. The project works on an automata-based learning system which models authors’ writing characters with automatons. Since there were pervious works done by Dr. T.Y. Lin and Ms. S.X. Zhang, we continue on ALERGIA algorithm analysis and initial common pattern study in this project. Although every author has his/her own writing style, such as sentence length and word frequency etc, there are always some similarities in writing style. We hypothesize that common strings fogged the expected test result, just like the noise in radio wave. This …
Extending Owl With Finite Automata Constraints, Jignesh Borisa
Extending Owl With Finite Automata Constraints, Jignesh Borisa
Master's Projects
The Web Ontology Language (OWL) is a markup language for sharing and publishing data using ontologies on the Internet. It belongs to a family of knowledge representation languages for writing ontologies. Answer Set Programming (ASP) is a declarative programming approach to knowledge representation. It is oriented towards difficult search problems. In this project, we developed an extension to OWL add support for collection class constraints. These constraints come in the form of membership checks for sets where these set are computed by finite automata. We developed an inference engine for the resulting language. This engine extends the Java-based Pellet library …