of paper 0269 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherl... more of paper 0269 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019.
The complexity of the instruction set of modern microprocessors often leads to faults in the micr... more The complexity of the instruction set of modern microprocessors often leads to faults in the microinstruction sequencing and timing errors in the implementation of the processor control. These errors are difficult to detect with conventional simulation methods. As an alternative, formal verification uses a mathematical model of the system to verify its correct behavior by constructing a formal proof. Recently we introduced a new partial order formal verification method based on the notion of series-parallel posets. The associated verification algorithms have a low order space- and time complexity, and have been successfully applied to the verification of properties of real-world systems such as the PCI local bus protocol and the MESI cache coherence protocol. In this paper we use series-parallel posets to model and verify the behavior of the DLX microprocessor control.
This paper presents a feature selection methodology for authorship attribution based on lexical s... more This paper presents a feature selection methodology for authorship attribution based on lexical stress patterns of words in text. The methodology uses part-of-speech information to make the proper selection of a lexical stress pattern when multiple possible pronunciations of the word exist. The selected lexical stress patterns are used to train machine learning classifiers to perform author attribution. The methodology is applied to a corpus of 18th century political texts, achieving a significant improvement in performance compared to previous work.
We present an investigation of the usefulness of consonance as a stylistic feature for author att... more We present an investigation of the usefulness of consonance as a stylistic feature for author attribution of historical texts. We describe an algorithm for extracting consonance from written text and a set of experiments using different classifiers to explore the accuracy of consonance-based attribution on a set of 18th-century documents and a collection of 19th-century literary works.
This paper presents a feature selection methodology for authorship attribution based on lexical s... more This paper presents a feature selection methodology for authorship attribution based on lexical stress patterns of words in text. The methodology uses part-of-speech information to make the proper selection of a lexical stress pattern when multiple possible pronunciations of the word exist. The selected lexical stress patterns are used to train machine learning classifiers to perform author attribution. The methodology is applied to a corpus of 18th century political texts, achieving a significant improvement in performance compared to previous work.
This paper describes our experience in creating and teaching an introductory, undergraduate Game ... more This paper describes our experience in creating and teaching an introductory, undergraduate Game Development course for non-Computer Science majors. The hands-on course uses the Unity game engine to teach a variety of Computer Science (CS) topics and inspire students to consider majoring in Computer Science. The paper discusses the course objectives, the approach to presenting the material, and the course outcomes in terms of student success and CS majors recruitment.
of paper 0269 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherl... more of paper 0269 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019.
The complexity of the instruction set of modern microprocessors often leads to faults in the micr... more The complexity of the instruction set of modern microprocessors often leads to faults in the microinstruction sequencing and timing errors in the implementation of the processor control. These errors are difficult to detect with conventional simulation methods. As an alternative, formal verification uses a mathematical model of the system to verify its correct behavior by constructing a formal proof. Recently we introduced a new partial order formal verification method based on the notion of series-parallel posets. The associated verification algorithms have a low order space- and time complexity, and have been successfully applied to the verification of properties of real-world systems such as the PCI local bus protocol and the MESI cache coherence protocol. In this paper we use series-parallel posets to model and verify the behavior of the DLX microprocessor control.
This paper presents a feature selection methodology for authorship attribution based on lexical s... more This paper presents a feature selection methodology for authorship attribution based on lexical stress patterns of words in text. The methodology uses part-of-speech information to make the proper selection of a lexical stress pattern when multiple possible pronunciations of the word exist. The selected lexical stress patterns are used to train machine learning classifiers to perform author attribution. The methodology is applied to a corpus of 18th century political texts, achieving a significant improvement in performance compared to previous work.
We present an investigation of the usefulness of consonance as a stylistic feature for author att... more We present an investigation of the usefulness of consonance as a stylistic feature for author attribution of historical texts. We describe an algorithm for extracting consonance from written text and a set of experiments using different classifiers to explore the accuracy of consonance-based attribution on a set of 18th-century documents and a collection of 19th-century literary works.
This paper presents a feature selection methodology for authorship attribution based on lexical s... more This paper presents a feature selection methodology for authorship attribution based on lexical stress patterns of words in text. The methodology uses part-of-speech information to make the proper selection of a lexical stress pattern when multiple possible pronunciations of the word exist. The selected lexical stress patterns are used to train machine learning classifiers to perform author attribution. The methodology is applied to a corpus of 18th century political texts, achieving a significant improvement in performance compared to previous work.
This paper describes our experience in creating and teaching an introductory, undergraduate Game ... more This paper describes our experience in creating and teaching an introductory, undergraduate Game Development course for non-Computer Science majors. The hands-on course uses the Unity game engine to teach a variety of Computer Science (CS) topics and inspire students to consider majoring in Computer Science. The paper discusses the course objectives, the approach to presenting the material, and the course outcomes in terms of student success and CS majors recruitment.
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Papers by Lubomir Ivanov