Citation Methodologies in Eusebius’ Historia ecclesiastica and Other Ancient Historiography

This dissertation examines ancient historiographic citation methodologies in light of Mikhail Bakhtin’s dichotomy between polyphony and monologization. In particular, this dissertation argues that Eusebius of Caesarea’s Historia ecclesiastica (HE) abandons the monologic citation methodology typical of previous Greek and Hellenistic historiography and introduces a polyphonic citation methodology that influences subsequent late-ancient Christian historiography to varying degrees. Whereas Pre-Eusebian Greek and Hellenistic historiographers typically use citations to support the single authorial consciousness of the historiographer, Eusebius uses citations to counterbalance his own shortcomings as a witness to past events. Eusebius allows his citations to retain their own voice, even when they conflict with his. The result is a narrative that transcends the point of view of any single individual and makes multiple witnesses, including the narrator, available to the reader. Post-Eusebian late-ancient Christian historiographers exhibit the influence of Eusebius’ innovation, but they are not as intentional as Eusebius in their use of citation methodologies. Many subsequent Christian historiographers use both monologic and polyphonic citation methodologies. Their tendency to follow Eusebius’ practice of citing numerous lengthy citations sometimes emphasizes points of view that oppose the author’s point of view. When an opposing viewpoint surfaces in enough citations, a polyphonic citation methodology emerges. The reader holds the two different narrative strands in tension as the author continues to give voice to opposing viewpoints. After illustrating the citation methodologies with passages from numerous Greek, Hellenistic, and late ancient Christian historiographers, this dissertation concludes with a short computational analysis that uses natural language processing to reveal some broad trends that highlight the previous findings and suggest a possibility for future research.

Electroencephalogram based Causality Graph Analysis in Behavior Tasks of Parkinson’s Disease Patients

Electroencephalographic (EEG) signals of the human brains represent electrical activities for a number of channels recorded over a the scalp. The main purpose of this thesis is to investigate the interactions and causality of different parts of a brain using EEG signals recorded during a performance subjects of verbal fluency tasks. Subjects who have Parkinson's Disease (PD) have difficulties with mental tasks, such as switching between one behavior task and another. The behavior tasks include phonemic fluency, semantic fluency, category semantic fluency and reading fluency. This method uses verbal generation skills, activating different Broca's areas of the Brodmann's areas (BA44 and BA45). Advanced signal processing techniques are used in order to determine the activated frequency bands in the granger causality for verbal fluency tasks. The graph learning technique for channel strength is used to characterize the complex graph of Granger causality. Also, the support vector machine (SVM) method is used for training a classifier between two subjects with PD and two healthy controls. Neural data from the study was recorded at the Colorado Neurological Institute (CNI). The study reveals significant difference between PD subjects and healthy controls in terms of brain connectivities in the Broca's Area BA44 and BA45 corresponding to EEG electrodes. The results in this thesis also demonstrate the possibility to classify based on the flow of information and causality in the brain of verbal fluency tasks. These methods have the potential to be applied in the future to identify pathological information flow and causality of neurological diseases.

Machine Translation: Translators' Friend or Foe?

This paper discusses the impact of machine translation on the language industry, specifically addressing its effect on translators. It summarizes the history of the development of machine translation, explains the underlying theory that ties machine translation to its practical applications, and describes the different types of machine translation as well as other tools familiar to translators. There are arguments for and against its use, as well as evaluation methods for testing it. Internet and real-time communication are featured for their role in the increase of machine translation use. The potential that this technology has in the future of professional translation is examined. This paper shows that machine translation will continue to be increasingly used whether translators like it or not.