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Fusing Multi-Abstraction Vector Space Models For Concern Localization, Yun ZHANG, David LO, Xin XIA, Giuseppe SCANNIELLO, Tien-Duy B. LE, Jianling SUN 2018 Singapore Management University

Fusing Multi-Abstraction Vector Space Models For Concern Localization, Yun Zhang, David Lo, Xin Xia, Giuseppe Scanniello, Tien-Duy B. Le, Jianling Sun

Research Collection School Of Information Systems

Concern localization refers to the process of locating code units that match a particular textual description. It takes as input textual documents such as bug reports and feature requests and outputs a list of candidate code units that are relevant to the bug reports or feature requests. Many information retrieval (IR) based concern localization techniques have been proposed in the literature. These techniques typically represent code units and textual descriptions as a bag of tokens at one level of abstraction, e.g., each token is a word, or each token is a topic. In this work, we propose a multi-abstraction ...


Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor 2018 University of Louisville

Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor

Electronic Theses and Dissertations

Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics ...


Customer Level Predictive Modeling For Accounts Receivable To Reduce Intervention Actions, Michelle L. F. Cheong, Wen SHI 2018 Singapore Management University

Customer Level Predictive Modeling For Accounts Receivable To Reduce Intervention Actions, Michelle L. F. Cheong, Wen Shi

Research Collection School Of Information Systems

One of the main costs associated with Accounts receivable (AR) collection is related to the intervention actions taken to remind customers to pay their outstanding invoices. Apart from the cost, intervention actions may lead to poor customer satisfaction, which is undesirable in a competitive industry. In this paper, we studied the payment behavior of invoices for customers of a logistics company, and used predictive modeling to predict if a customer will pay the outstanding invoices with high probability, in an attempt to reduce intervention actions taken, thus reducing cost and improving customer relationship. We defined a pureness measure to classify ...


Leveraging Tiled Display For Big Data Visualization Using D3.Js, Ujjwal Acharya 2018 Boise State University

Leveraging Tiled Display For Big Data Visualization Using D3.Js, Ujjwal Acharya

Boise State University Theses and Dissertations

Data visualization has proven effective at detecting patterns and drawing inferences from raw data by transforming it into visual representations. As data grows large, visualizing it faces two major challenges: 1) limited resolution i.e. a screen is limited to a few million pixels but the data can have a billion data points, and 2) computational load i.e. processing of this data becomes computationally challenging for a single node system. This work addresses both of these issues for efficient big data visualization. In the developed system, a High Pixel Density and Large Format display was used enabling the display ...


Detecting Saliency By Combining Speech And Object Detection In Indoor Environments, Kiran Thapa 2018 Boise State University

Detecting Saliency By Combining Speech And Object Detection In Indoor Environments, Kiran Thapa

Boise State University Theses and Dissertations

Describing scenes such as rooms, city streets, or routes, is a very common human task that requires the ability to identify and describe the scene sufficiently for a hearer to develop a mental model of the scene. When people talk about such scenes, they mention some objects of the scene at the exclusion of others. We call the mentioned objects salient objects as people consider them noticeable or important in comparison to other non-mentioned objects. In this thesis, we look at saliency of visual scenes and how visual saliency informs what can and should be said about a scene when ...


Why Accountants Should Embrace Machine Learning?, Benjamin Huan Zhou LEE, Gary PAN, Poh Sun SEOW 2018 Singapore Management University

Why Accountants Should Embrace Machine Learning?, Benjamin Huan Zhou Lee, Gary Pan, Poh Sun Seow

Research Collection School Of Accountancy

AI and ML are enabling tools that take the tedious gruntwork out of accounting, freeing up professionals to provide valuable insights - as well as professional scepticism - which are sought-after services no machine can replicate.


A Fine-Grained Attribute Based Data Retrieval With Proxy Re-Encryption Scheme For Data Outsourcing Systems, Hanshu HONG, Ximeng LIU, Zhixin SUN 2018 Singapore Management University

A Fine-Grained Attribute Based Data Retrieval With Proxy Re-Encryption Scheme For Data Outsourcing Systems, Hanshu Hong, Ximeng Liu, Zhixin Sun

Research Collection School Of Information Systems

Attribute based encryption is suitable for data protection in data outsourcing systems such as cloud computing. However, the leveraging of encryption technique may retrain some routine operations over the encrypted data, particularly in the field of data retrieval. This paper presents an attribute based date retrieval with proxy re-encryption (ABDR-PRE) to provide both fine-grained access control and retrieval over the ciphertexts. The proposed scheme achieves fine-grained data access management by adopting KP-ABE mechanism, a delegator can generate the re-encryption key and search indexes for the ciphertexts to be shared over the target delegatee’s attributes. Throughout the process of data ...


Evaluation Of Drug-Loaded Gold Nanoparticle Cytotoxicity As A Function Of Tumor Tissue Heterogeneity., Hunter Allan Miller 2018 University of Louisville

Evaluation Of Drug-Loaded Gold Nanoparticle Cytotoxicity As A Function Of Tumor Tissue Heterogeneity., Hunter Allan Miller

Electronic Theses and Dissertations

The inherent heterogeneity of tumor tissue presents a major challenge to nanoparticle-medicated drug delivery. This heterogeneity spans from the molecular to the cellular (cell types) and to the tissue (vasculature, extra-cellular matrix) scales. Here we employ computational modeling to evaluate therapeutic response as a function of vascular-induced tumor tissue heterogeneity. Using data with three-layered gold nanoparticles loaded with cisplatin, nanotherapy is simulated with different levels of tissue heterogeneity, and the treatment response is measured in terms of tumor regression. The results show that tumor vascular density non-trivially influences the nanoparticle uptake and washout, and the associated tissue response. The drug ...


Chaff From The Wheat: Characterizing And Determining Valid Bug Reports, Yuanrui FAN, Xin XIA, David LO, Ahmed E. HASSAN 2018 Singapore Management University

Chaff From The Wheat: Characterizing And Determining Valid Bug Reports, Yuanrui Fan, Xin Xia, David Lo, Ahmed E. Hassan

Research Collection School Of Information Systems

Developers use bug reports to triage and fix bugs. When triaging a bug report, developers must decide whether the bug report is valid (i.e., a real bug). A large amount of bug reports are submitted every day, with many of them end up being invalid reports. Manually determining valid bug report is a difficult and tedious task. Thus, an approach that can automatically analyze the validity of a bug report and determine whether a report is valid can help developers prioritize their triaging tasks and avoid wasting time and effort on invalid bug reports.


A Bi-Encoder Lstm Model For Learning Unstructured Dialogs, Diwanshu Shekhar 2018 University of Denver

A Bi-Encoder Lstm Model For Learning Unstructured Dialogs, Diwanshu Shekhar

Electronic Theses and Dissertations

Creating a data-driven model that is trained on a large dataset of unstructured dialogs is a crucial step in developing a Retrieval-based Chatbot systems. This thesis presents a Long Short Term Memory (LSTM) based Recurrent Neural Network architecture that learns unstructured multi-turn dialogs and provides implementation results on the task of selecting the best response from a collection of given responses. Ubuntu Dialog Corpus Version 2 (UDCv2) was used as the corpus for training. Ryan et al. (2015) explored learning models such as TF-IDF (Term Frequency-Inverse Document Frequency), Recurrent Neural Network (RNN) and a Dual Encoder (DE) based on Long ...


Improving The Accuracy Of Mobile Touchscreen Qwerty Keyboards, Amanda Kirk 2018 University of Denver

Improving The Accuracy Of Mobile Touchscreen Qwerty Keyboards, Amanda Kirk

Electronic Theses and Dissertations

In this thesis we explore alternative keyboard layouts in hopes of finding one that increases the accuracy of text input on mobile touchscreen devices. In particular, we investigate if a single swap of 2 keys can significantly improve accuracy on mobile touchscreen QWERTY keyboards. We do so by carefully considering the placement of keys, exploiting a specific vulnerability that occurs within a keyboard layout, namely, that the placement of particular keys next to others may be increasing errors when typing. We simulate the act of typing on a mobile touchscreen QWERTY keyboard, beginning with modeling the typographical errors that can ...


Use Of Verified Twitter Accounts During Crisis Events, Kai Anderson 2018 Utah State University

Use Of Verified Twitter Accounts During Crisis Events, Kai Anderson

All Graduate Theses and Dissertations

This thesis reports on the use of verified Twitter accounts during crisis events. Twitter is a social media platform that allows users to broadcast and exchange public text messages and it can be used as a communication tool during crisis events. Verified Twitter accounts are those accounts that Twitter has investigated and found to be genuinely maintained by the claimed owner. Celebrities, public officials, and other well-known persons or companies often seek this account status. The owners of these accounts are likely to provide more accurate or relevant information during a crisis event because they represent a brand, whether themselves ...


A Deep Learning Approach To Recognizing Bees In Video Analysis Of Bee Traffic, Astha Tiwari 2018 Utah State University

A Deep Learning Approach To Recognizing Bees In Video Analysis Of Bee Traffic, Astha Tiwari

All Graduate Theses and Dissertations

Colony Collapse Disorder (CCD) has been a major threat to bee colonies around the world which affects vital human food crop pollination. The decline in bee population can have tragic consequences, for humans as well as the bees and the ecosystem. Bee health has been a cause of urgent concern for farmers and scientists around the world for at least a decade but a specific cause for the phenomenon has yet to be conclusively identified.

This work uses Artificial Intelligence and Computer Vision approaches to develop and analyze techniques to help in continuous monitoring of bee traffic which will further ...


Word Recognition In Nutrition Labels With Convolutional Neural Network, Anuj Khasgiwala 2018 Utah State University

Word Recognition In Nutrition Labels With Convolutional Neural Network, Anuj Khasgiwala

All Graduate Theses and Dissertations

Nowadays, everyone is very busy and running around trying to maintain a balance between their work life and family, as the working hours are increasing day by day. In such hassled life people either ignore or do not give enough attention to a healthy diet. An imperative part of a healthy eating routine is the cognizance and maintenance of nourishing data and comprehension of how extraordinary sustenance and nutritious constituents influence our bodies. Besides in the USA, in many other countries, nutritional information is fundamentally passed on to consumers through nutrition labels (NLs) which can be found in all packaged ...


Teaching Landscape Construction Using Augmented Reality, Arshdeep Singh 2018 Utah State University

Teaching Landscape Construction Using Augmented Reality, Arshdeep Singh

All Graduate Theses and Dissertations

This thesis describes the design, development, and evaluation of an interactive Microsoft HoloLens application that projects landscape models in Augmented Reality. The application was developed using the Unity framework and 3D models created in Sketchup. Using the application, students can not only visualize the models in real space but can also interact with the models using gestures. The students can interact with the models using gaze and air-tap gestures.

Application testing was conducted with 21 students from the Landscape Architecture and Environmental Planning department at Utah State University. To evaluate the application, students completed a usability survey after using the ...


A Novel Multirobot System For Distributed Phenotyping, Tianshuang Gao, Homagni Saha, Hamid Emadi, Jiaoping Zhang, Alec Lofquist, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh Singh, Sourabh Bhattacharya 2018 Iowa State University

A Novel Multirobot System For Distributed Phenotyping, Tianshuang Gao, Homagni Saha, Hamid Emadi, Jiaoping Zhang, Alec Lofquist, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh Singh, Sourabh Bhattacharya

Mechanical Engineering Publications

Phenotypic studies require large datasets for accurate inference and prediction. Collecting plant data in a farm can be very labor intensive and costly. This paper presents the design, architecture (hardware and software) and deployment of a distributed modular agricultural multi-robot system for row crop field data collection. The proposed system has been deployed in a soybean research farm at Iowa State University.


Lightweight Call-Graph Construction For Multilingual Software Analysis, Anne-Marie Bogar, Damian Lyons, David Baird 2018 Fordham University

Lightweight Call-Graph Construction For Multilingual Software Analysis, Anne-Marie Bogar, Damian Lyons, David Baird

Faculty Publications

Analysis of multilingual codebases is a topic of increasing importance. In prior work, we have proposed the MLSA (MultiLingual Software Analysis) architecture, an approach to the lightweight analysis of multilingual codebases, and have shown how it can be used to address the challenge of constructing a single call graph from multilingual software with mutual calls. This paper addresses the challenge of constructing monolingual call graphs in a lightweight manner (consistent with the objective of MLSA) which nonetheless yields sufficient information for resolving language interoperability calls. A novel approach is proposed which leverages information from a ...


Man, Machine, Scientific Models And Creation Science, Steven M. Gollmer 2018 Cedarville University

Man, Machine, Scientific Models And Creation Science, Steven M. Gollmer

The Proceedings of the International Conference on Creationism

Historically, physics was the most quantitative of the sciences. Geologists and biologists built their models based on observation, categorization and generalization. This distinction between qualitative and quantitative sciences prompted the quote attributed to Ernest Rutherford that “All science is either physics or stamp collecting.” In the intervening 80 years all sciences have exploded in the use of quantitative measures to find patterns and trends in data. A review of a half-century of creationist literature shows that this transition has not been lost to the creationist community.

As this trend continues to accelerate, two areas of caution need to be taken ...


Adam And Eve, Designed Diversity, And Allele Frequencies, John C. Sanford, Robert W. Carter, Wes Brewer, John Baumgardner, Bruce Potter, Jon Potter 2018 FMS Foundation

Adam And Eve, Designed Diversity, And Allele Frequencies, John C. Sanford, Robert W. Carter, Wes Brewer, John Baumgardner, Bruce Potter, Jon Potter

The Proceedings of the International Conference on Creationism

Theistic evolutionists present multiple genetic arguments against a literal Adam and Eve. One key argument asserts it would be impossible for a single human couple to give rise to the genetic diversity seen in the modern human population. This implicitly assumes Adam and Eve would have been created without internal genetic diversity. If this were true, all observed variations would have to arise recently via random mutations. This would require incredibly high mutation rates, logically leading to rapid extinction.

Yet, Adam and Eve could have been created massively heterozygous. We have argued for over a decade that they could have ...


International Data Sources & Data Literacy, Lisa DeLuca 2018 Seton Hall University

International Data Sources & Data Literacy, Lisa Deluca

Lisa DeLuca, MLIS, MPA

No abstract provided.


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