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Newton’S Third Law In Karmic Warfare, Kazmier Maślanka Nov 2016

Newton’S Third Law In Karmic Warfare, Kazmier Maślanka

The Transdisciplinary STEAM+ Journal

A work entitled "Newton's Third Law in Karmic Warfare" is a mathematical visual poem which is a perfect example of a technique, that I call The Paradigm Poem. This piece makes a direct connection with the concept of karma and Newton’s Third Law of motion. I will introduce the concept of “The Mathematical Paradigm Poem” to illuminate an example of how metaphor is used in mathematical visual poetry. I will also discuss much of the process in making this aesthetic expression.

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Towards A Computational Model Of Frame Of Reference Alignment In Swedish Dialogue, Simon Dobnik, Christine Howes, Kim Demaret, John D. Kelleher Nov 2016

Towards A Computational Model Of Frame Of Reference Alignment In Swedish Dialogue, Simon Dobnik, Christine Howes, Kim Demaret, John D. Kelleher

Conference papers

In this paper we examine how people negotiate, interpret and repair the frame of reference (FoR) in online text based dialogues discussing spatial scenes in Swedish. We describe work-in-progress in which participants are given different perspectives of the same scene and asked to locate several objects that are only shown on one of their pictures. This task requires participants to coordinate on FoR in order to identify the missing objects. This study has implications for situated dialogue systems.

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Towards Deeper Understanding In Neuroimaging, Rex Devon Hjelm Nov 2016

Towards Deeper Understanding In Neuroimaging, Rex Devon Hjelm

Computer Science ETDs

Neuroimaging is a growing domain of research, with advances in machine learning having tremendous potential to expand understanding in neuroscience and improve public health. Deep neural networks have recently and rapidly achieved historic success in numerous domains, and as a consequence have completely redefined the landscape of automated learners, giving promise of significant advances in numerous domains of research. Despite recent advances and advantages over traditional machine learning methods, deep neural networks have yet to have permeated significantly into neuroscience studies, particularly as a tool for discovery. This dissertation presents well-established and novel tools for unsupervised learning which aid in …

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Estimating The Parameter Of Exponential Distribution Under Type Ii Censoring From Fuzzy Data, Iman Makhdoom, Parviz Nasiri, Abbas Pak Nov 2016

Estimating The Parameter Of Exponential Distribution Under Type Ii Censoring From Fuzzy Data, Iman Makhdoom, Parviz Nasiri, Abbas Pak

Journal of Modern Applied Statistical Methods

The problem of estimating the parameter of Exponential distribution on the basis of type II censoring scheme is considered when the available data are in the form of fuzzy numbers. The Bayes estimate of the unknown parameter is obtained by using the approximation forms of Lindley (1980) and Tierney and Kadane (1986) under the assumption of gamma prior. The highest posterior density (HPD) estimate of the parameter of interest is found. A Monte Carlo simulation is used to compare the performances of the different methods. A real data set is investigated to illustrate the applicability of …

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Testing Point Null Hypothesis Of A Normal Mean And The Truth: 21st Century Perspective, Calyampudi Radhakrishna Rao, Miodrag M. Lovric Nov 2016

Testing Point Null Hypothesis Of A Normal Mean And The Truth: 21st Century Perspective, Calyampudi Radhakrishna Rao, Miodrag M. Lovric

Journal of Modern Applied Statistical Methods

Testing a point (sharp) null hypothesis is arguably the most widely used statistical inferential procedure in many fields of scientific research, nevertheless, the most controversial, and misapprehended. Since 1935 when Buchanan-Wollaston raised the first criticism against hypothesis testing, this foundational field of statistics has drawn increasingly active and stronger opposition, including draconian suggestions that statistical significance testing should be abandoned or even banned. Statisticians should stop ignoring these accumulated and significant anomalies within the current point-null hypotheses paradigm and rebuild healthy foundations of statistical science. The foundation for a paradigm shift in testing statistical hypotheses is suggested, which is testing …

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Automatic Pain Assessment From Infants’ Crying Sounds, Chih-Yun Pai Nov 2016

Automatic Pain Assessment From Infants’ Crying Sounds, Chih-Yun Pai

USF Tampa Graduate Theses and Dissertations

Crying is infants utilize to express their emotional state. It provides the parents and the nurses a criterion to understand infants’ physiology state. Many researchers have analyzed infants’ crying sounds to diagnose specific diseases or define the reasons for crying. This thesis presents an automatic crying level assessment system to classify infants’ crying sounds that have been recorded under realistic conditions in the Neonatal Intensive Care Unit (NICU) as whimpering or vigorous crying. To analyze the crying signal, Welch’s method and Linear Predictive Coding (LPC) are used to extract spectral features; the average and the standard deviation of the frequency …

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Vol. 15, No. 2 (Full Issue), Jmasm Editors Nov 2016

Vol. 15, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

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Learning Sentence Embeddings With Auxiliary Tasks For Cross-Domain Sentiment Classification, Jianfei Yu, Jing Jiang Nov 2016

Learning Sentence Embeddings With Auxiliary Tasks For Cross-Domain Sentiment Classification, Jianfei Yu, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we study cross-domain sentiment classification with neural network architectures. We borrow the idea from Structural Correspondence Learning and use two auxiliary tasks to help induce a sentence embedding that supposedly works well across domains for sentiment classification. We also propose to jointly learn this sentence embedding together with the sentiment classifier itself. Experiment results demonstrate that our proposed joint model outperforms several state-of-the-art methods on five benchmark datasets.

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Landmark Reranking For Smart Travel Guide Systems By Combining And Analyzing Diverse Media, Junge Shen, Jialie Shen, Tao Mei, Xinbo Gao Nov 2016

Landmark Reranking For Smart Travel Guide Systems By Combining And Analyzing Diverse Media, Junge Shen, Jialie Shen, Tao Mei, Xinbo Gao

Research Collection School Of Computing and Information Systems

Advanced networking technologies and massive online social media have stimulated a booming growth of travel heterogeneous information in recent years. By employing such information, smart travel guide systems, such as landmark ranking systems, have been proposed to offer diverse online travel services. It is essential for a landmark ranking system to structure, analyze, and search the travel heterogeneous information to produce human-expected results. Therefore, currently the most fundamental yet challenging problems can be concluded: 1) how to fuse heterogeneous tourism information and 2) how to model landmark ranking. In this paper, a novel landmark search system is introduced based on …

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Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao Nov 2016

Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao

Research Collection School Of Computing and Information Systems

Product reviews greatly influence purchase decisions in online shopping. A common burden of online shopping is that consumers have to search for the right answers through massive reviews, especially on popular products. Hence, estimating and predicting the helpfulness of reviews become important tasks to directly improve shopping experience. In this paper, we propose a new approach to helpfulness prediction by leveraging aspect analysis of reviews. Our hypothesis is that a helpful review will cover many aspects of a product at different emphasis levels. The first step to tackle this problem is to extract proper aspects. Because related products share common …

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Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo Nov 2016

Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo

Research Collection School Of Computing and Information Systems

Social media provides a convenient way for customers to express their feedback to companies. Identifying different types of customers based on their feedback behavior can help companies to maintain their customers. In this paper, we use a machine learning approach to predict a customer’s feedback behavior based on her first feedback tweet. First, we identify a few categories of customers based on their feedback frequency and the sentiment of the feedback. We identify three main categories: spiteful, one-off, and kind. Next, we build a model to predict the category of a customer given her first feedback. We use profile and …

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On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim Nov 2016

On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The popularity of social media platforms such as Twitter has led to the proliferation of automated bots, creating both opportunities and challenges in information dissemination, user engagements, and quality of services. Past works on profiling bots had been focused largely on malicious bots, with the assumption that these bots should be removed. In this work, however, we find many bots that are benign, and propose a new, broader categorization of bots based on their behaviors. This includes broadcast, consumption, and spam bots. To facilitate comprehensive analyses of bots and how they compare to human accounts, we develop a systematic profiling …

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Fuzzy Logic Controlofgantry Crane System, Betim Shabani Oct 2016

Fuzzy Logic Controlofgantry Crane System, Betim Shabani

UBT International Conference

The use of gantry crane systems for transporting payload is very common in industrial application. However, moving the payload using the crane is not an easy task especially when strict specifications on the swing angle and on the transfer time need to be satisfied. To overcome this problem, an intelligent gantry crane system had been introduced. Fuzzy logic controllers were adopted, designed and implemented for controlling payload position as well as the swing angle of the gantry crane. Fuzzy logic defines rules that determine the behavior of the system using word descriptions instead of mathematical equations also fuzzy logic control …

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Fundamentals Of Machine Learning For Neural Machine Translation, John D. Kelleher Oct 2016

Fundamentals Of Machine Learning For Neural Machine Translation, John D. Kelleher

Conference papers

This paper presents a short introduction to neural networks and how they are used for machine translation and concludes with some discussion on the current research challenges being addressed by neural machine translation (NMT) research. The primary goal of this paper is to give a no-tears introduction to NMT to readers that do not have a computer science or mathematical background. The secondary goal is to provide the reader with a deep enough understanding of NMT that they can appreciate the strengths of weaknesses of the technology. The paper starts with a brief introduction to standard feed-forward neural networks (what …

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Cover Text Steganography: N-Gram And Entropy-Based Approach, Sara M. Rico-Larmer Oct 2016

Cover Text Steganography: N-Gram And Entropy-Based Approach, Sara M. Rico-Larmer

KSU Proceedings on Cybersecurity Education, Research and Practice

Steganography is an ancient technique for hiding a secret message within ordinary looking messages or objects (e.g., images), also known as cover messages. Among various techniques, hiding text data in plain text file is a challenging task due to lack of redundant information. This paper proposes two new approaches to embed a secret message in a cover text document. The two approaches are n-gram and entropy metric-based generation of stego text. We provide examples of encoding secret messages in a cover text document followed by an initial evaluation of how well stego texts look close to the plain …

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The Role Of Perception In Situated Spatial Reference, John D. Kelleher Oct 2016

The Role Of Perception In Situated Spatial Reference, John D. Kelleher

Conference papers

This position paper set out the argument that an interesting avenue of exploration and study of universals and variation in spatial reference is to address this topic in termsa of the universals in human perception and attention and to explore how these universals impact on spatial reference across cultures and languages.

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Mining Mixed-Initiative Dialogs, Saverio Perugini Oct 2016

Mining Mixed-Initiative Dialogs, Saverio Perugini

Computer Science Faculty Publications

Human-computer dialogs are an important vehicle through which to produce a rich and compelling form of human-computer interaction. We view the specification of a human-computer dialog as a set of sequences of progressive interactions between a user and a computer system, and mine partially ordered sets, which correspond to mixing dialog initiative, embedded in these sets of sequences—a process we refer to as dialog mining—because partially ordered sets can be advantageously exploited to reduce the control complexity of a dialog implementation. Our mining losslessly compresses the specification of a dialog. We describe our mining algorithm and report the results of …

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Development And Semantic Exploitation Of A Relational Data Model For Service Delivery In South African Municipalities, Kgotatso Desmond Mogotlane, Jean Vincent Fonou Dombeu Oct 2016

Development And Semantic Exploitation Of A Relational Data Model For Service Delivery In South African Municipalities, Kgotatso Desmond Mogotlane, Jean Vincent Fonou Dombeu

The African Journal of Information Systems

Relational databases (RDB) are the main sources of structured data for government institutions and businesses. Since these databases are dependent on autonomous hardware and software they create problems of data integration and interoperability. Solutions have been proposed to convert RDB into ontology to enable their sharing, reuse and integration on the Semantic Web. However, the proposed methods and techniques remain highly technical and there is lack of research that focuses on the empirical application of these methods and techniques in information systems (IS) domains. This study develops and semantically exploits a relational data model of the South African Municipalities Information …

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The Persistence And Characteristics Of Chinook Salmon Migrations To The Upper Klamath River Prior To Exclusion By Dams, John B. Hamilton, Dennis W. Rondorf, William R. Tinniswood, Ryan J. Leary, Tim Mayer, Charleen Gavette, Lynne A. Casal Oct 2016

The Persistence And Characteristics Of Chinook Salmon Migrations To The Upper Klamath River Prior To Exclusion By Dams, John B. Hamilton, Dennis W. Rondorf, William R. Tinniswood, Ryan J. Leary, Tim Mayer, Charleen Gavette, Lynne A. Casal

Wildland Resources Faculty Publications

In this research article, John Hamilton and his co-authors present extensive new research and information gathered since a 2005 publication on the historical evidence of anadromomous fish distribution in the Upper Klamath River watershed. Using historical accounts from early explorers and ethnographers to early-twentieth-century photographs, newspaper accounts, and government reports, the authors provide a more complete record of past salmon migrations. The updated record “substantiate[s] the historical persistence of salmon, their migration characteristics, and the broad population baseline that will be key to future commercial, recreational, and Tribal fisheries in the Klamath River and beyond.” During a time when salmon …

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Tracking Virality And Susceptibility In Social Media, Tuan Anh Hoang, Ee-Peng Lim Oct 2016

Tracking Virality And Susceptibility In Social Media, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In social media, the magnitude of information propagation hinges on the virality and susceptibility of users spreading and receiving the information respectively, as well as the virality of information items. These users' and items' behavioral factors evolve dynamically at the same time interacting with one another. Previous works however measure the factors statically and independently in a restricted case: each user has only a single adoption on each item, and/or users' exposure to items are observable. In this work, we investigate the inter-relationship among the factors and users' multiple adoptions on items to propose both new static and temporal models …

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Table Of Contents Sep 2016

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

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Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington Sep 2016

Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington

Journal of Digital Forensics, Security and Law

Empirical and anecdotal evidence indicates that cyberharassment is more prevalent as the use of social media becomes increasingly widespread, making geography and physical proximity irrelevant. Cyberharassment can take different forms (e.g., cyberbullying, cyberstalking, cybertrolling), and be motivated by the objectives of inflicting distress, exercising control, impersonation, and defamation. Little is currently known about the modus operandi of offenders and their psychological characteristics. Investigation of these behaviours is particularly challenging because it involves digital evidence distributed across the devices of both alleged offenders and victims, as well as online service providers, sometimes over an extended period of time. This special issue …

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Back Matter Sep 2016

Back Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

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Front Matter Sep 2016

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

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Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron Sep 2016

Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron

Journal of Digital Forensics, Security and Law

Threats are communicative acts, but it is not always obvious what they communicate or when they communicate imminent credible and serious risk. This paper proposes a research- and theory-based set of over 20 potential linguistic risk indicators that may discriminate credible from non-credible threats within online threat message corpora. Two prongs are proposed: (1) Using expert and layperson ratings to validate subjective scales in relation to annotated known risk messages, and (2) Using the resulting annotated corpora for automated machine learning with computational linguistic analyses to classify non-threats, false threats, and credible threats. Rating scales are proposed, existing threat corpora …

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In Continuity With The Past: Indigenous Environmentalism And Indian Christian Visions Of Flora, James Ponniah Sep 2016

In Continuity With The Past: Indigenous Environmentalism And Indian Christian Visions Of Flora, James Ponniah

Journal of Global Catholicism

This article considers whether Indian Christianity can be said to have a distinctive ecological vision. The first two parts of the article examine Christian environmentalism in two native forms of Indian Christianity: Tamil Christianity and Tribal Christianity. Continuing with the theme of conformity to the local culture—though of the elite—the third part of the article investigates how Christian Ashrams function as dynamic centers for ecological praxis. The last part of the article considers how contemporary Indian Christian communities can respond to the ecological challenges confronting them.

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Preliminaries To A Study Of Stance In News Broadcasts, Nigel Ward Sep 2016

Preliminaries To A Study Of Stance In News Broadcasts, Nigel Ward

Departmental Technical Reports (CS)

Aspects of stance have significant potential for information retrieval and filtering. This technical report is about stance in radio news broadcast, and is intended primarily to motivate and document details of the data and annotations used in the work reported in Inferring Stance from Prosody (Ward et al., 2016). It describes the process of identifying 14 important aspects of stance, describes two corpora for investigating stance, describes the annotation of those corpora, presents some preliminary observations, and lists a set of useful prosodic features.

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Extracting Food Substitutes From Food Diary Via Distributional Similarity, Palakorn Achananuparp, Ingmar Weber Sep 2016

Extracting Food Substitutes From Food Diary Via Distributional Similarity, Palakorn Achananuparp, Ingmar Weber

Research Collection School Of Computing and Information Systems

In this paper, we explore the problem of identifying substitute relationship between food pairs from real-world food consumption data as the first step towards the healthier food recommendation. Our method is inspired by the distributional hypothesis in linguistics. Specifically, we assume that foods that are consumed in similar contexts are more likely to be similar dietarily. For example, a turkey sandwich can be considered a suitable substitute for a chicken sandwich if both tend to be consumed with french fries and salad. To evaluate our method, we constructed a real-world food consumption dataset from MyFitnessPal's public food diary entries and …

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Towards A Deep Learning-Based Activity Discovery System, Eoin Rogers, John D. Kelleher, Robert J. Ross Sep 2016

Towards A Deep Learning-Based Activity Discovery System, Eoin Rogers, John D. Kelleher, Robert J. Ross

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 activity discovery based on modern deep learning techniques. We hypothesise that our proposed approach can deal with interleaved datasets in a more intelligent manner than most existing AD methods. We also build upon prior work building hierarchies of activities that capture the inherent ag- gregate nature of complex activities and show how this could plausibly be adapted to work with the deep learning technique we present. Finally, we …

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When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim Sep 2016

When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Microblogging services such as Twitter and Sina Weibo have been an important, if not indespensible, platform for people around the world to connect to one another. The rich content and user interactions on these platforms reveal insightful information about each user that are valuable for various real-life applications. In particular, user offline relationships, especially those intimate ones such as family members and couples, offer distinctive value for many business and social settings. In this study, we focus on using Sina Weibo to discover intimate offline relationships among users. The problem is uniquely interesting and challenging due to the difficulty in …

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