Firebird Database Backup by Serialized Database Table Dump

This paper presents a simple data dump and load utility for Firebird databases which mimics mysqldump in MySQL. This utility, fb_dump and fb_load, for dumping and loading respectively, retrieves each database table using kinterbasdb and serializes the data using marshal module. This utility has two advantages over the standard Firebird database backup utility, gbak. Firstly, it is able to backup and restore single database tables which might help to recover corrupted databases. Secondly, the output is in text-coded format (from marshal module) making it more resilient than a compressed text backup, as in the case of using gbak.Comment: 5 page

An Artificial Life Simulation Library Based on Genetic Algorithm, 3-Character Genetic Code and Biological Hierarchy

Genetic algorithm (GA) is inspired by biological evolution of genetic organisms by optimizing the genotypic combinations encoded within each individual with the help of evolutionary operators, suggesting that GA may be a suitable model for studying real-life evolutionary processes. This paper describes the design of a Python library for artificial life simulation, Digital Organism Simulation Environment (DOSE), based on GA and biological hierarchy starting from genetic sequence to population. A 3-character instruction set that does not take any operand is introduced as genetic code for digital organism. This mimics the 3-nucleotide codon structure in naturally occurring DNA. In addition, the context of a 3-dimensional world composing of ecological cells is introduced to simulate a physical ecosystem. Using DOSE, an experiment to examine the changes in genetic sequences with respect to mutation rates is presented

Ragaraja 1.0: The Genome Interpreter of Digital Organism Simulation Environment (DOSE)

This manuscript documents the implementation of Ragaraja interpreter version 1.0, the 3-character genetic code interpreter in Digital Organisms Simulation Environment (DOSE). These codes are licensed under Python Software Foundation License version 2

NotaLogger: Notarization Code Generator and Logging Service

The act of affixing a signature and date to a document, known as notarization, is often used as evidence for sighting or bearing witness to any documents in question. Notarization and dating are required to render documents admissible in the court of law. However, the weakest link in the process of notarization is the notary; that is, the person dating and affixing his/her signature. A number of legal cases had shown instances of false dating and falsification of signatures. In this study, NotaLogger is proposed, which can be used to generate a notarization code to be appended to the document to be notarized. During notarization code generation, the user can include relevant information to identify the document to be notarized and the date and time of code generation will be logged into the system. Generated and used notarization code can be verified by searching in NotaLogger, and such search will result in date time stamping by a Network Time Protocol server. As a result, NotaLogger can be used as an independent witness to any notarizations. NotaLogger can be accessed at http://mauricelab.pythonanywhere.com/notalogger/

An Artificial Life Simulation Library Based on Genetic Algorithm, 3-Character Genetic Code and Biological Hierarchy

Genetic algorithm (GA) is inspired by biological evolution of genetic organisms by optimizing the genotypic combinations encoded within each individual with the help of evolutionary operators, suggesting that GA may be a suitable model for studying real-life evolutionary processes. This paper describes the design of a Python library for artificial life simulation, Digital Organism Simulation Environment (DOSE), based on GA and biological hierarchy starting from genetic sequence to population. A 3-character instruction set that does not take any operand is introduced as genetic code for digital organism. This mimics the 3-nucleotide codon structure in naturally occurring DNA. In addition, the context of a 3-dimensional world composing of ecological cells is introduced to simulate a physical ecosystem. Using DOSE, an experiment to examine the changes in genetic sequences with respect to mutation rates is presented