Computer Systems Lab TJHSST Current Projects In-House, pt 6

2 Current Projects, pt. 6 In-House Algorithms for Computational Comparative Historical Linguistics Optimizing Genetic Algorithms for Cypher Decoding Decision Trees for Career Guidance Archival of Articles via RSS and Datamining Performed on Stored Articles Sabermetric Statistics in Baseball

3 Algorithms for Computational Comparative Historical Linguistics Over time, languages change by regular, systematic processes. It is possible, by looking at the state of a language now and in the past, to deduce the exact changes that occurred, and the order in which they occurred. These changes also split languages, therefore it is also possible to, by using modern languages as input, induce the probable structure of their parent language. My goal is to develop algorithms by which computers may efficiently analyze the historical structure of languages and language families.

4 Optimizing Genetic Algorithms for Cypher Decoding Over the past several years, genetic algorithms have come into wide use because of their ability to find good solutions to computing problems very quickly. They imitate nature by crossing over strings of information represented as chromosomes, with preference given to the more fit solutions produced. They hold great promise in the field of cryptology, where they may be used to quickly find good partial solutions, thus eliminating much of the intense manual labor that goes into identifying initial coding schemes.

5 Decision Trees for Career Guidance This research project will be an investigation into the design and implementation of various decision trees for career guidance. A decision tree takes into account some sort of situation outlined by a group of parameters and outputs a Boolean decision to the situation. This project will take into account many aspects associated with decision trees including database building, searching and sorting, and algorithms for accessing data. My project utilizes numerous decision trees in an effort to serve as a tool for career guidance for young adults. A user will fill out a form of specified fields that will then be analyzed by the group of decision trees until a field of study/occupation is given to the user as the outcome. This group of decision trees will be built through database building techniques.

6 Archival of Articles via RSS and Datamining Performed on Stored Articles RSS (Really Simple Syndication, encompassing Rich Site Summary and RDF Site Summary) is a web syndication protocol used by many blogs and news websites to distribute information it saves people having to visit several sites repeatedly to check for new content. At this point in time there are many RSS newsfeed aggregators available to the public, but none of them perform any sort of archival of information beyond the RSS metadata. The purpose of this project is to create an RSS aggregator that will archive the text of the actual articles linked to in the RSS feeds in some kind of linkable, searchable database, and, if all goes well, implement some sort of datamining capability as well.

7 An Analysis of Sabermetric Statistics in Baseball For years, baseball theorists have pondered the most basic question of baseball statistics: which statistic most accurately predicts which team will win a baseball game. With this information, baseball teams can rely on technological, statistical-based scouting organizations. The book, Moneyball addresses the advent of sabermetric statistics in the 1980s and 1990s and shows how radical baseball thinkers instituted a new era of baseball scouting and player analyzation. This project analyzes which baseball statistic is the single most important. It has been found that new formulas, such as OBP, OPS, and Runs Created correlate better with the number of runs a team scores than traditional statistics such as batting average.