Digital Commons Network^™

Classically Biased: A Quantitative Analysis Of Gender & Writing Styles In Classical Literature, Madeleine Rose Delcambre

Honors Theses

This thesis is a first attempt in assessing patterns related to gender in classical literature prior to the 21st century, specifically looking at the way writing styles and language di↵er among female and male authors; e.g., sentence structuring, lexical diversity, and dictionary similarities. Further topics of analysis included gender distribution and sentiment within the novels themselves. Seventy-eight open-source novels were used in the analysis, with thirty-one books by female authors and forty-seven by male authors. Data from the novels was acquired using Python, natural language processing, and the Natural Language Toolkit (NLTK). Graphs and visuals were then created to summarize …

Bigger Versus Similar: Selecting A Background Corpus For First Story Detection Based On Distributional Similarity, Fei Wang, Robert J. Ross, John D. Kelleher

Articles

The current state of the art for First Story Detection (FSD) are nearest neighbourbased models with traditional term vector representations; however, one challenge faced by FSD models is that the document representation is usually defined by the vocabulary and term frequency from a background corpus. Consequently, the ideal background corpus should arguably be both large-scale to ensure adequate term coverage, and similar to the target domain in terms of the language distribution. However, given these two factors cannot always be mutually satisfied, in this paper we examine whether the distributional similarity of common terms is more important than the scale …

Successful Strategies For Using Knowledge Management In Small And Medium-Sized Enterprises, Josephine Kayaga Nsubuga-Mugoa

Walden Dissertations and Doctoral Studies

Knowledge management (KM) is vital for an organization to succeed in a highly dynamic and competitive world. The purpose of this multiple case study was to explore strategies that managers of small and medium-sized enterprises (SMEs) use to effectively integrate KM into business practices. The study population comprised 5 managers from 2 SMEs operating in Uganda. The eligibility criteria for this study were that participants had to be from Ugandan SMEs with a knowledge-intensive environment, managers with some responsibility of KM in the organization, and experienced with at least 1 year of successful KM practices. The conceptual framework for this …

Abusive And Hate Speech Tweets Detection With Text Generation, Abhishek Nalamothu

Browse all Theses and Dissertations

According to a Pew Research study, 41% of Americans have personally experienced online harassment and two-thirds of Americans have witnessed harassment in 2017. Hence, online harassment detection is vital for securing and sustaining the popularity and viability of online social networks. Machine learning techniques play a crucial role in automatic harassment detection. One of the challenges of using supervised approaches is training data imbalance. Existing text generation techniques can help augment the training data, but they are still inadequate and ineffective. This research explores the role of domain-specific knowledge to complement the limited training data available for training a text …

Llvm-Ir Based Decompilation, Ilsoo Jeon

Browse all Theses and Dissertations

Decompilation is a process of transforming an executable program into a source-like high-level language code, which plays an important role in malware analysis, and vulnerability detection. In this thesis, we design and implement the middle end of a decompiler framework, focusing on Low Level Language properties reduction using the optimization techniques, propagation and elimination. An open-source software tool, dagger, is used to translate binary code to LLVM (Low Level Virtual Machine) Intermediate Representation code. We perform data flow analysis and control flow analysis on the LLVM format code to generate high-level code using a Functional Programming Langauge (FPL), Haskell. The …

Machine Learning Methods For The Analysis Of Clinical Conversation, Md Mehedi Hasan

Wayne State University Dissertations

Motivational Interviewing (MI) is an evidence-based communication technique to increase intrinsic motivation and self-efficacy for behavior change. This goal is achieved through the exploration of the patient's own desires, ability, reasons, need for and commitment to the targeted behavior change. However, communication science approaches to understanding the efficacy of MI are inherently limited by traditional qualitative coding methods which is a time-consuming and resource-intensive process. Thus, an efficient method is required to automate the coding process which will accelerate the pace of communication research in behavioral science. The specific provider behaviors responsible for the elicitation of change talk, are also …

Crowdsourcing Image Schemas, Dagmar Gromann, Jamie C. Macbeth

Computer Science: Faculty Publications

With their potential to map experiental structures from the sensorimotor to the abstract cognitive realm, image schemas are believed to provide an embodied grounding to our cognitive conceptual system, including natural language. Few empirical studies have evaluated humans’ intuitive understanding of image schemas or the coherence of image-schematic annotations of natural language. In this paper we present the results of a human-subjects study in which 100 participants annotate 12 simple English sentences with one or more image schemas. We find that human subjects recruited from a crowdsourcing platform can understand image schema descriptions and use them to perform annotations of …

Using Mobile Learning Tools In Higher Education: A Uae Case, Jenny Eppard, Zeina Hojeij, Pinar Ozdemir-Ayber, Marlieke Rodjan-Helder, Sandra Baroudi

All Works

© International Association of Online Engineering. Research indicates that mobile learning (ML), has the potential to transform teaching and learning. Despite its benefits, mobile learning adoption is a challenging process which requires support to facilitate its integration. The focus of this article is to investigate the factors that could affect ML acceptance. The quantitative and qualitative data collected from the surveys revealed additional information regarding the pedagogical benefits of and obstacles to mobile learning integration. Even though participants in this study reported to be late adopters of technology, they maintained that ML is useful for learning, specifically ubiquitous learning. Teachers …

Kbot: Knowledge-Enabled Personalized Chatbot For Self-Management Of Asthma In Pediatric Population, Dipesh Kadariya

Browse all Theses and Dissertations

Asthma, chronic pulmonary disease, is one of the major health issues in the United States. Given its chronic nature, the demand for continuous monitoring of patient’s adherence to the medication care plan, assessment of their environment triggers, and management of asthma control level can be challenging in traditional clinical settings and taxing on clinical professionals. A shift from a reactive to a proactive asthma care can improve health outcomes and reduce expenses. On the technology spectrum, smart conversational systems and Internet-of-Things (IoTs) are rapidly gaining popularity in the healthcare industry. By leveraging such technological prevalence, it is feasible to design …

Knowledge Graph Reasoning Over Unseen Rdf Data, Bhargavacharan Reddy Kaithi

Browse all Theses and Dissertations

In recent years, the research in deep learning and knowledge engineering has made a wide impact on the data and knowledge representations. The research in knowledge engineering has frequently focused on modeling the high level human cognitive abilities, such as reasoning, making inferences, and validation. Semantic Web Technologies and Deep Learning have an interest in creating intelligent artifacts. Deep learning is a set of machine learning algorithms that attempt to model data representations through many layers of non-linear transformations. Deep learning is in- creasingly employed to analyze various knowledge representations mentioned in Semantic Web and provides better results for Semantic …

Data-Driven And Knowledge-Based Strategies For Realizing Crowd Wisdom On Social Media, Shreyansh Bhatt

Browse all Theses and Dissertations

The wisdom of the crowd is a well-known example of collective intelligence wherein an aggregated judgment of a group of individuals is superior to that of an individual. The aggregated judgment is surprisingly accurate for predicting the outcome of a range of tasks from geopolitical forecasting to the stock price prediction. Recent research has shown that participants' previous performance data contributes to the identification of a subset of participants that can collectively predict an accurate outcome. In the absence of such performance data, researchers have explored the role of human-perceived diversity, i.e., whether a human considers a crowd as a …

A Novel Methodology For Timely Brain Formations Of 3d Spatial Information With Application To Visually Impaired Navigation, Spyridon Manganas

Browse all Theses and Dissertations

Human brain analysis and understanding pose several challenges due to the great complexity of the structural organization and the functional connectivity that characterizes the human brain. The ability of the brain to adapt in dynamic changes over time such as normal aging, neurodegenerative diseases or congenital brain malformations renders the brain’s exploration a particularly demanding and difficult task. In recent years, advances in brain imaging modalities and lately the multimodal fusion, combined with improvements in related technologies have greatly assisted the development of brain maps by providing insights regarding the overall brain structure and functionality. Even though the existence of …

The Second Decade Of Numeracy: Entering The Seas Of Literacy, H. L. Vacher

Numeracy

This multipurpose editorial explores and tries to count the many types of literacy that are referred to by name in Wikipedia and Numeracy. Wikipedia’s Category:Literacy page identifies 44 kinds of literacy that are the subject of articles, ranging from numeracy and graphicacy to braille literacy and diaspora literacy. In addition, searching Google finds more than 30 adjective-literacy or noun-literacy collocations, including quantitative literacy, adult literacy, and document literacy, that do not have Wikipedia pages of their own but are mentioned on other Wikipedia pages. The sum puts this modest literacy count in line with the more than 70 bodies …

Detection Of Offensive Youtube Comments, A Performance Comparison Of Deep Learning Approaches, Priyam Bansal

Dissertations

Social media data is open, free and available in massive quantities. However, there is a significant limitation in making sense of this data because of its high volume, variety, uncertain veracity, velocity, value and variability. This work provides a comprehensive framework of text processing and analysis performed on YouTube comments having offensive and non-offensive contents.

YouTube is a platform where every age group of people logs in and finds the type of content that most appeals to them. Apart from this, a massive increase in the use of offensive language has been apparent. As there are massive volume of new …

Explainable Neural Networks Based Anomaly Detection For Cyber-Physical Systems, Kasun Amarasinghe

Theses and Dissertations

Cyber-Physical Systems (CPSs) are the core of modern critical infrastructure (e.g. power-grids) and securing them is of paramount importance. Anomaly detection in data is crucial for CPS security. While Artificial Neural Networks (ANNs) are strong candidates for the task, they are seldom deployed in safety-critical domains due to the perception that ANNs are black-boxes. Therefore, to leverage ANNs in CPSs, cracking open the black box through explanation is essential.

The main objective of this dissertation is developing explainable ANN-based Anomaly Detection Systems for Cyber-Physical Systems (CP-ADS). The main objective was broken down into three sub-objectives: 1) Identifying key-requirements that an …

Determining Political Inclination In Tweets Using Transfer Learning, Mehtab Iqbal

College of Graduate Studies: Theses & Dissertations

Last few years have seen tremendous development in neural language modeling for transfer learning and downstream applications. In this research, I used Howard and Ruder’s Universal Language Model Fine Tuning (ULMFiT) pipeline to develop a classifier that can determine whether a tweet is politically left leaning or right leaning by likening the content to tweets posted by @TheDemocrats or @GOP accounts on Twitter. We achieved 87.7% accuracy in predicting political ideological inclination.

The Role Of Previous Discourse In Identifying Public Textual Cyberbullying, Aurelia Power, Anthony Keane, Brian Nolan, Brian O'Neill

Articles

In this paper we investigate the contribution of previous discourse in identifying elements that are key to detecting public textual cyberbullying. Based on the analysis of our dataset, we first discuss the missing cyberbullying elements and the grammatical structures representative of discourse-dependent cyberbullying discourse. Then we identify four types of discourse dependent cyberbullying constructions: (1) fully inferable constructions, (2) personal marker and cyberbullying link inferable constructions, (3) dysphemistic element and cyberbullying link inferable constructions, and (4) dysphemistic element inferable constructions. Finally, we formalise a framework to resolve the missing cyberbullying elements that proposes several resolution algorithms. The resolution algorithms target …

A Comparative Study Of Author Gender Identification, Tuğba Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, author gender identification has gained considerable attention in the fields of information retrieval and computational linguistics. In this paper, we employ and evaluate different learning approaches based on machine learning (ML) and neural network language models to address the problem of author gender identification. First, several ML classifiers are applied to the features obtained by bag-of-words. Secondly, datasets are represented by a low-dimensional real-valued vector using Word2vec, GloVe, and Doc2vec, which are on par with ML classifiers in terms of accuracy. Lastly, neural networks architectures, the convolution neural network and recurrent neural network, are trained and their …

Real-Time Implementation Of Electronic Power Transformer Based On Intelligentcontroller, Hakan Açikgöz, Ökkeş Fati̇h Keçeci̇oğlu, Mustafa Şekkeli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Along with the rapid advances in power electronics and semiconductor technology, electronic power transformers (EPTs), which are expected to replace conventional power transformers in the future, are being developed and designed. This study presents the dynamic performance of the intelligent controller structure in the control of an EPT. The EPT structure, consisting of the input, isolation, and output stages, is designed for experimental and simulation studies. A three-phase pulse width modulation (PWM) rectifier is used to rectify the grid voltages at the input stage of EPT. The DC-bus voltage of the three-phase PWM rectifier is controlled by a neuro-fuzzy controller …

Automatic Generation Control Analysis Of Power System With Nonlinearities Andelectric Vehicle Aggregators With Time-Varying Delay Implementing A Novel Control Strategy, Nimai Charan Patel, Binod Kumar Sahu, Manoj Kumar Debnath

Turkish Journal of Electrical Engineering and Computer Sciences

Automatic generation control (AGC) also known as load frequency control plays a vital role in interconnected power system for frequency regulation. Electric vehicles (EVs) with battery as the storage device can participate in frequency regulation service. In practice, a large number of EVs are aggregated as a single unit called EV aggregator for participation in frequency regulation service in AGC system. Participation of EV aggregators in AGC system for frequency regulation will be encouraged in near future because EVs have less environmental pollution than the conventional vehicles. However, participation of EV aggregators in AGC system may introduce time delay which …

Extracting Accent Information From Urdu Speech For Forensic Speaker Recognition, Falak Tahir, Sajid Saleem, Ayaz Ahmad

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a new method for extraction of accent information from Urdu speech signals. Accent is used in speaker recognition system especially in forensic cases and plays a vital role in discriminating people of different groups, communities and origins due to their different speaking styles. The proposed method is based on Gaussian mixture model-universal background model (GMM-UBM), mel-frequency cepstral coefficients (MFCC), and a data augmentation (DA) process. The DA process appends features to base MFCC features and improves the accent extraction and forensic speaker recognition performances of GMM-UBM. Experiments are performed on an Urdu forensic speaker corpus. The experimental …

Sentence Similarity Using Weighted Path And Similarity Matrices, Reza Javadzadeh, Morteza Zahedi, Marziea Rahimi

Turkish Journal of Electrical Engineering and Computer Sciences

Sentence similarity is the task of assessing how similar the two snippets of text are. Similarity techniques are used extensively in clustering, summarization, classification, plagiarism detection etc. Due to a small set of vocabularies, sentence similarity is considered to be a difficult problem in natural language processing. There are two issues in solving this problem: (1) Which similarity techniques to be used for word pair similarity and (2) How to generalize that to sentence pairs. We have used the weighted path, a WordNet-based similarity assessment, and the paraphrase database to obtain word pair similarity values. Thereafter, we extracted maximum values …

Trmor: A Finite-State-Based Morphological Analyzer For Turkish, Ayla Kayabaş, Helmut Schmi̇d, Ahmet Ercan Topcu, Özkan Kiliç

Turkish Journal of Electrical Engineering and Computer Sciences

Morphological analysis is an important component of natural language processing systems like spelling correction tools, parsers, machine translation systems, and dictionary tools. In this paper, we present TRMOR, a morphological analyzer for Turkish, which uses the SFST tool (Stuttgart Finite-State Transducer). TRMOR can be freely used for academic research (see http://www.cis.uni-muenchen.de/~schmid/tools/SFST/). It covers a large part of Turkish morphology including inflection, derivation, and some compounding. It uses morphotactic and morphophonological rules and a stem lexicon. We describe the morphological structure of Turkish, explain the phonological and morphological rules implemented in TRMOR, evaluate the system, and test it in special cases. …

Natural Environment Associations With Mental Health And Obesity Status, Adam Edwin London

Walden Dissertations and Doctoral Studies

Mental health and obesity were ranked among the health priorities of the 2014 and 2017 Community Health Needs Assessments in Kent County, Michigan. Exposure to nature is correlated to improved health outcomes across a variety of morbidities including poor mental health and obesity. This cross-sectional study set within the frameworks of attention restoration theory, environmental health, and pathways to health benefits from nature assessed county survey data including self-reported nature exposures/interactions separated into 3 domain areas: access to nature, attitudes about nature, and physical activity in nature or in nature-based activities. Binary logistic regression analyses of the 653 respondents found …

Sustainable Business Growth: An Exploration Of Ghanaian Small Business Survival, John W. Atanga

Walden Dissertations and Doctoral Studies

Small businesses are significant contributors to a nation’s job creation and employment. These enterprises face many challenges that often lead to failure within 5 years. Some small business owners fail because they lack the necessary strategies for maintaining a sustainable business operation. The purpose of this qualitative descriptive phenomenological study was to analyze how to overcome the high failure rate of small businesses in Accra, Ghana. The conceptual framework for this study was institutional and planned behavior theories. The research questions sought participant’s experiences with small business survival that may have led to sustainable businesses. Data were collected from 20 …

A Hott Approach To Computational Effects, Phillip A. Wells

Senior Independent Study Theses

A computational effect is any mutation of real-world state that occurs as the result of a computation. We develop a model for describing computational effects within homotopy type theory, a branch of mathematics separate from other foundations such as set theory. Such a model allows us to describe programs as total functions over values while preserving information about the effects those programs induce.

The D&D Sorting Hat: Predicting Dungeons And Dragons Characters From Textual Backstories, Joseph C. Macinnes

Senior Independent Study Theses

Dungeons and Dragons is a tabletop roleplaying game which focuses heavily on character interaction and creating narratives. The current state of the game's character creation process often bogs down new players in decisions related to game mechanics, not a character's identity and personality. This independent study investigates the use of machine learning and natural language processing to make these decisions for a player based on their character's backstory - the textual biography or description of a character. The study presents a collection of existing characters and uses these examples to create a family of models capable of predicting a character's …

Front Matter

The Synapse: Intercollegiate science magazine

No abstract provided.

Fact Sheet, Yale University Office Of Institutional Research

Fact Sheets

No abstract provided.

Emergence: Developing Worldview In The Environmental Humanities, Rhonda D. Davis

Antioch University Dissertations & Theses

While the environment has long played a role in humanistic expressions and investigations, the need for a more integrated look at the human-environment relationship has become ever more pressing. More than ever, humanities scholars are recognizing their ability to mobilize critical and creative action to address pressing socioeconomic, sociopolitical, and socioenvironmental problems. Teaching and engaging students through interdisciplinary methods, connecting students and communities, developing a sense of agency and responsibility for planetary sustainability has become a visible focus in higher education. My study aimed to understand how an environmental humanities class affects, if at all, the way students construct worldview. …