Digital Commons Network^™

On-Demand Deep Model Compression For Mobile Devices: A Usage-Driven Model Selection Framework, Sicong Liu, Yingyan Lin, Zimu Zhou, Kaiming Nan, Hui Liu, Junzhao Du

Research Collection School Of Computing and Information Systems

Recent research has demonstrated the potential of deploying deep neural networks (DNNs) on resource-constrained mobile platforms by trimming down the network complexity using different compression techniques. The current practice only investigate stand-alone compression schemes even though each compression technique may be well suited only for certain types of DNN layers. Also, these compression techniques are optimized merely for the inference accuracy of DNNs, without explicitly considering other application-driven system performance (e.g. latency and energy cost) and the varying resource availabilities across platforms (e.g. storage and processing capability). In this paper, we explore the desirable tradeoff between performance and resource constraints …

Application Of The Entropy Concept To Thermodynamics And Life Sciences: Evolution Parallels Thermodynamics, Cellulose Hydrolysis Thermodynamics, And Ordered And Disordered Vacancies Thermodynamics, Marko Popovic

Theses and Dissertations

Entropy, first introduced in thermodynamics, is used in a wide range of fields. Chapter 1 discusses some important theoretical and practical aspects of entropy: what is entropy, is it subjective or objective, and how to properly apply it to living organisms. Chapter 2 presents applications of entropy to evolution. Chapter 3 shows how cellulosic biofuel production can be improved. Chapter 4 shows how lattice vacancies influence the thermodynamic properties of materials. To determine the nature of thermodynamic entropy, Chapters 1 and 2 describe the roots, the conceptual history of entropy, as well as its path of development and application. From …

Radical Social Ecology As Deep Pragmatism: A Call To The Abolition Of Systemic Dissonance And The Minimization Of Entropic Chaos, Arielle Brender

Student Theses 2015-Present

This paper aims to shed light on the dissonance caused by the superimposition of Dominant Human Systems on Natural Systems. I highlight the synthetic nature of Dominant Human Systems as egoic and linguistic phenomenon manufactured by a mere portion of the human population, which renders them inherently oppressive unto peoples and landscapes whose wisdom were barred from the design process. In pursuing a radical pragmatic approach to mending the simultaneous oppression and destruction of the human being and the earth, I highlight the necessity of minimizing entropic chaos caused by excess energy expenditure, an essential feature of systems that aim …

Non-Use Of A Mobile Phone During Conducting Crime Can Also Be Evidential, Vinod Polpaya Bhattathiripad Ph D

Annual ADFSL Conference on Digital Forensics, Security and Law

Cyber-clever criminals who are aware of the consequence of using mobile phones during conducting crimes often stay away from their phones while involved in crimes. Some of them even change their handset and SIM card, subsequently. This article looks into how, intentional disassociation (and even unintentional non-use) of mobile phone in (non-cyber) crimes, can become evidential clues of the perpetrators’ involvement in criminal acts. With the help of a recent judicial episode, this article reveals how extremely careful and masterful handling of extensive and voluminous Call Details Records and tower dumps by a cyber-savvy investigating official can unearth evidential clues …

Breaking The Language Barrier: Equitable Assessment In General Chemistry, Eshani Lee

UNLV Theses, Dissertations, Professional Papers, and Capstones

Because language provides the framework through which knowledge is constructed, it is crucial to consider the ways in which students with limited English proficiencies are able to express their understanding. English language learners (ELLs) make up a significant portion of the student body in the education system and represent many ethnic and racial minorities in STEM (Science, Technology, Engineering & Mathematics) fields (Burke & Mattis, 2007). Despite the national push to build a more diversified, STEM-ready workforce, there is little research that considers the way ELLs are assessed in STEM courses at the postsecondary level. Literature reports that science tests …

What’S At Steak? The Political Discourse Of Emissions Intensity And Implications Of Animal Agriculture, Kalyn Simon

Master's Theses

This thesis analyzes the international discourse of greenhouse gas emissions in relation to livestock production. Specific government ministries, research institutes, and multilateral organizations are framing a new strategy to mitigate emissions by using emissions intensity metrics. Emissions intensity is a ratio comparing emissions produced per unit of animal product as oppose to measuring absolute emissions. This research is acknowledged as a win-win scenario which allows for a reduction of greenhouse gas emissions while continuing production more efficiently. This thesis outlines the emergence of this metric in international discourse and the implications this shift has on the livestock sector globally. Ultimately, …

Automatic Conversation Review For Intelligent Virtual Assistants, Ian R. Beaver

Computer Science ETDs

When reviewing the performance of Intelligent Virtual Assistants (IVAs), it is desirable to prioritize conversations involving misunderstood human inputs. These conversations uncover error in natural language understanding and help prioritize and expedite improvements to the IVA. As human reviewer time is valuable and manual analysis is time consuming, prioritizing the conversations where misunderstanding has likely occurred reduces costs and speeds improvement. A system for measuring the posthoc risk of missed intent associated with a single human input is presented. Numerous indicators of risk are explored and implemented. These indicators are combined using various means and evaluated on real world data. …

The Arts And Technology: How Educational Technology Can Bring Humanities Further Into Elementary And Primary School Systems, Coleman D. Alameda

Senior Theses

As the world becomes more inclined to implement technology in nearly every aspect of society, the United States Department of Education must find a way to incorporate new styles of modern and high-tech teaching without pushing out certain subjects from its curriculum. I believe technology can be used to bring the Humanities further into the classroom. In today’s society American education programs are desperately trying to make up for subpar primary school scores in mathematics and science. According to the government accredited international education forum (the Organization for Economic Co-operation and Development) the United States was found to be below …

Supporting English Language Learners Inside The Mathematics Classroom: One Teacher’S Unique Perspective Working With Students During Their First Years In America, Amy Marie Fendrick

Research and Evaluation in Education, Technology, Art, and Design

Reflecting upon my personal experiences teaching mathematics to English Language Learners (ELL) in a public high school in Lincoln, Nebraska, this essay largely focuses on the time I spent as the only Accelerated Math teacher in my school building. From 2012 – 2017, I taught three different subjects at this high school: Advanced Algebra, Algebra, and Accelerated Math. This essay highlights why I chose to become a math and ELL teacher, as well as the challenges, issues, struggles, and successes I experienced during my time teaching. I focus on the challenges I faced teaching students who did not share my …

Classifying Controversiality In Article Data, Kateryna Kaplun

Theses, Dissertations and Culminating Projects

The paper presents a statistical analysis that explores methods for measuring con- troversy in online news articles collected from 23 RSS feeds. Several baseline datasets are used to re-evaluate previous work and determine the predictive quality of uni- grams for classifying controversial documents. This is achieved by comparing con-troversy and sentiment, exploring sentiment variance, and considering entropy and standard deviation as potential features. The paper tests whether there are more controversial words in negative sentiment than in positive sentiment as well as whether there are more non-controversial words in positive sentiment than in negative sen-timent. Unlike previous studies, we determine …

Proverbial Machine Translation: Translating Proverbs Between Spanish And English Using Phrased Based Statistical Machine Translation With The Grammatical Category Based Approach, Teneala Spencer

Honors Theses

The focus of the research presented in the paper is translating the non-literal interpretation of proverbs from Spanish to English without changing their intended meaning. Proverbs have limited variation in comparison to slang, poetry, and metaphors which tend to differ significantly within the context that they are used. Although there are many other approaches for machine translation (MT), the one most suitable for the research project is Phrased Based Statistical Machine translation used in conjunction with the Grammatical Category- Based approach.

Al Planning Assistant For Scheduling Daily Activities, Priyanka Ahuja

Theses and Dissertations

Artificial conversational agents are software agents that can interact with humans in the way humans do. Siri Cortana, and Alexa are examples of intelligent agents that can help us with almost all the basic tasks. These agents are smart enough to do the basic tasks, but not as much when it comes to complex tasks, such as analyzing traffic data, reviewing scheduling conflicts, rescheduling meetings while resolving conflicts, and offering suggestions based upon data analyses (e.g. traffic patterns, weather, etc.) The actual potential of dialogue-based task agent potential remains untapped. The reason is the fact agents lack the ability to …

Hierarchical Learning Of Cross-Language Mappings Through Distributed Vector Representations For Code, Nghi D. Q. Bui, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Translating a program written in one programming language to another can be useful for software development tasks that need functionality implementations in different languages. Although past studies have considered this problem, they may be either specific to the language grammars, or specific to certain kinds of code elements (e.g., tokens, phrases, API uses). This paper proposes a new approach to automatically learn cross-language representations for various kinds of structural code elements that may be used for program translation. Our key idea is two folded: First, we normalize and enrich code token streams with additional structural and semantic information, and train …

Deep Code Comment Generation, Xing Hu, Ge Li, Xin Xia, David Lo, Zhi Jin

Research Collection School Of Computing and Information Systems

During software maintenance, code comments help developerscomprehend programs and reduce additional time spent on readingand navigating source code. Unfortunately, these comments areoften mismatched, missing or outdated in the software projects.Developers have to infer the functionality from the source code.This paper proposes a new approach named DeepCom to automatically generate code comments for Java methods. The generatedcomments aim to help developers understand the functionalityof Java methods. DeepCom applies Natural Language Processing(NLP) techniques to learn from a large code corpus and generatescomments from learned features. We use a deep neural networkthat analyzes structural information of Java methods for bettercomments generation. We conduct …

Entity Summarization Of Reviews And Micro-Reviews, Thanh Son Nguyen

Dissertations and Theses Collection (Open Access)

Along with the regular review content, there is a new type of user-generated content arising from the prevalence of mobile devices and social media, that is micro-review. Micro-reviews are bite-size reviews (usually under 200 char- acters), commonly posted on social media or check-in services, using a mobile device. They capture the immediate reaction of users, and they are rich in information, concise, and to the point. Both reviews and micro-reviews are useful for users to get to know the entity of interest, thus facilitating users in making their decision of purchasing or dining. However, the abundant number of both reviews …

Subword Spotting And Its Applications, Brian Lafayette Davis

Theses and Dissertations

We propose subword spotting, a generalization of word spotting where the search is for groups of characters within words. We present a method for performing subword spotting based on state-of-the-art word spotting techniques and evaluate its performance at three granularitires (unigrams, bigrams and trigrams) on two datasets.We demonstrate three applications of subword spotting, though others may exist. The first is assisting human transcribers identify unrecognized characters by locating them in other words. The second is searching for suffixes directly in word images (suffix spotting). And the third is computer assisted transcription (semi-automated transcription). We investigate several variations of computer assisted …

Evaluating Sequence Discovery Systems In An Abstraction-Aware Manner, Eoin Rogers, Robert J. Ross, John D. Kelleher

Conference papers

Activity discovery is a challenging machine learning problem where we seek to uncover new or altered behavioural patterns in sensor data. In this paper we motivate and introduce a novel approach to evaluating activity discovery systems. Pre-annotated ground truths, often used to evaluate the performance of such systems on existing datasets, may exist at different levels of abstraction to the output of the output produced by the system. We propose a method for detecting and dealing with this situation, allowing for useful ground truth comparisons. This work has applications for activity discovery, and also for related fields. For example, it …

Parameterizing And Aggregating Activation Functions In Deep Neural Networks, Luke Benjamin Godfrey

Graduate Theses and Dissertations

The nonlinear activation functions applied by each neuron in a neural network are essential for making neural networks powerful representational models. If these are omitted, even deep neural networks reduce to simple linear regression due to the fact that a linear combination of linear combinations is still a linear combination. In much of the existing literature on neural networks, just one or two activation functions are selected for the entire network, even though the use of heterogenous activation functions has been shown to produce superior results in some cases. Even less often employed are activation functions that can adapt their …

Evidence Aggregation For Answer Re-Ranking In Open-Domain Question Answering, Shuohang Wang, Mo Yu, Jing Jiang, Wei Zhang, Xiaoxiao Guo, Shiyu Chang, Zhiguo Wang, Tim Klinger, Gerald Tesauro, Murray Campbell

Research Collection School Of Computing and Information Systems

A popular recent approach to answering open-domain questions is to first search for question-related passages and then apply reading comprehension models to extract answers. Existing methods usually extract answers from single passages independently. But some questions require a combination of evidence from across different sources to answer correctly. In this paper, we propose two models which make use of multiple passages to generate their answers. Both use an answer-reranking approach which reorders the answer candidates generated by an existing state-of-the-art QA model. We propose two methods, namely, strength-based re-ranking and coverage-based re-ranking, to make use of the aggregated evidence from …

Adaptation And Augmentation: Towards Better Rescoring Strategies For Automatic Speech Recognition And Spoken Term Detection, Min Ma

Dissertations, Theses, and Capstone Projects

Selecting the best prediction from a set of candidates is an essential problem for many spoken language processing tasks, including automatic speech recognition (ASR) and spoken keyword spotting (KWS). Generally, the selection is determined by a confidence score assigned to each candidate. Calibrating these confidence scores (i.e., rescoring them) could make better selections and improve the system performance. This dissertation focuses on using tailored language models to rescore ASR hypotheses as well as keyword search results for ASR-based KWS.

This dissertation introduces three kinds of rescoring techniques: (1) Freezing most model parameters while fine-tuning the output layer in order to …

Multimodal Depression Detection: An Investigation Of Features And Fusion Techniques For Automated Systems, Michelle Renee Morales

Dissertations, Theses, and Capstone Projects

Depression is a serious illness that affects a large portion of the world’s population. Given the large effect it has on society, it is evident that depression is a serious health issue. This thesis evaluates, at length, how technology may aid in assessing depression. We present an in-depth investigation of features and fusion techniques for depression detection systems. We also present OpenMM: a novel tool for multimodal feature extraction. Lastly, we present novel techniques for multimodal fusion. The contributions of this work add considerably to our knowledge of depression detection systems and have the potential to improve future systems by …

On Rugina’S System Of Thought, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This article investigates Rugina's orientation table and gives particular examples for several of its seven models. Leon Walras's Economics of Stable Equilibrium and Keynes's Economics of Disequilibrium are combined in Rugina's orientation table in systems which are s percent stable and 100 ÿ s percent unstable, where s may be 100, 95, 65, 50, 35, 5, and 0. Classical logic and modern logic are united in Rugina's integrated logic, and then generalized in neutrosophic logic.

Cognitive Virtual Admissions Counselor, Kumar Raja Guvindan Raju, Cory Adams, Raghuram Srinivas

SMU Data Science Review

Abstract. In this paper, we present a cognitive virtual admissions counselor for the Master of Science in Data Science program at Southern Methodist University. The virtual admissions counselor is a system capable of providing potential students accurate information at the time that they want to know it. After the evaluation of multiple technologies, Amazon’s LEX was selected to serve as the core technology for the virtual counselor chatbot. Student surveys were leveraged to collect and generate training data to deploy the natural language capability. The cognitive virtual admissions counselor platform is currently capable of providing an end-to-end conversational dialog to …

Mapping Ordinances And Tweets Using Smart City Characteristics To Aid Opinion Mining, Manish Puri, Xu Du, Aparna S. Varde, Gerard De Melo

Department of Computer Science Faculty Scholarship and Creative Works

This research focuses on mining ordinances (local laws) and public reactions to them expressed on social media. We place particular emphasis on ordinances and tweets relating to Smart City Characteristics (SCCs), since an important aim of our work is to assess how well a given region heads towards a Smart City. We rely on SCCs as a nexus between a seemingly infinite number of ordinances and tweets to be able to map them, and also to facilitate SCC-based opinion mining later for providing feedback to urban agencies based on public reactions. Common sense knowledge is harnessed in our approach to …

2018 - The Twenty-Third Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Twenty-third Annual Symposium of Student Scholars, held on April 19, 2018. Includes abstracts from the presentations and posters.

Downscaling Africa’S Drought Forecasts Through Integration Of Indigenous And Scientific Drought Forecasts Using Fuzzy Cognitive Maps, Muthoni Masinde, Mwanjele Mwagha, Tsegaye Tadesse

National Drought Mitigation Center: Faculty Publications

In the wake of increased drought occurrences being witnessed in Sub-Saharan Africa, more localized and contextualized drought mitigation strategies are on the agendas of many researchers and policy makers in the region. The integration of indigenous knowledge on droughts with seasonal climate forecasts is one such strategy. The main challenge facing this integration, however, is the formal representation of highly-structured and holistic indigenous knowledge. In this paper, we demonstrate how the use of fuzzy cognitive mapping can address this challenge. Indigenous knowledge on droughts from five communities was modeled and represented using fuzzy cognitive maps. Maps from one of these …

An Investigation Into The Properties Of Quaternions: Their Origin, Basic Properties, Functional Analysis, And Algebraic Characteristics, James Miller

Masters Essays

No abstract provided.

Automatic Analysis Of Musical Lyrics, Joanna Gormley

Honors Senior Capstone Projects

Is music getting less sophisticated over time? That is the question which this study aims to answer, with the goal of improving upon previous analysis done on the topic. The blog posts which inspired this project lacked accuracy and dimensionality. Realizing that a larger data set of songs would make a significant difference in the precision of our analysis, we set out to design a piece of software constructed with the capability to analyze several thousand songs. Mimicking previous works which analyzed sophistication of music, the software focuses on the lyrics of songs. Three metrics were used in order to …

Support Assurance-Based Software Development For Mission Critical Domains Using The Model Driven Architecture, Chung-Ling Lin

Dissertations

In the past decades, software development for mission critical applications has drawn great attention not only in various mission critical communities but also software engineering communities. One of the important reasons is that the failure of these systems can lead to some serious consequences such as huge financial loss and even loss of life. Therefore, software certification has become an important activity for mission critical applications in that software assurance for such a system should be certified. With the increasing complexity of a software system in mission critical sectors, certifiers have found hard time to understand how a software system …

Ontology Based Technical Skill Similarity, Yeshwanth Bashyam Balachander

Master's Projects

Online job boards have become a major platform for technical talent procurement and job search. These job portals have given rise to challenging matching and search problems. The core matching or search happens between technical skills of the job requirements and the candidate's profile or keywords. The extensive list of technical skills and its polyonymous nature makes it less effective to perform a direct keyword matching. This results in substandard job matching or search results which misses out a closely matching candidate on account of it not having the exact skills. It is important to use a semantic similarity measure …