Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, 2021 Singapore Management University
Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng Xia, Reshika P. Velumani, Yong Wang, Huamin Qu, Xiaojuan Ma
Research Collection School Of Computing and Information Systems
With the rapid development of online education in recent years, there has been an increasing number of learning platforms that provide students with multi-step questions to cultivate their problem-solving skills. To guarantee the high quality of such learning materials, question designers need to inspect how students’ problem-solving processes unfold step by step to infer whether students’ problem-solving logic matches their design intent. They also need to compare the behaviors of different groups (e.g., students from different grades) to distribute questions to students with the right level of knowledge. The availability of fine-grained interaction data, such as mouse movement trajectories ...
An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, 2021 CUNY Graduate Center
An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja
Publications and Research
Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today’s data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap of knowledge in how ML systems actually evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed ...
Asynchronous Validations Using Programming Contracts In Java, 2021 San Jose State University
Asynchronous Validations Using Programming Contracts In Java, Rahul Shukla
Design by Contract is a software development methodology based on the idea of having contracts between two software components. Programming contracts are invariants specified as pre-conditions and post-conditions. The client component must ensure that all the pre-conditions are satisfied before calling the server component. The server component must guarantee the post-conditions are met before the call returns to the client component. Current work in Design by Contract in Java focuses on writing shorthand contracts using annotations that are processed serially.
Modern software systems require a lot of business rules validations on complicated domain objects. Often, such validations are in the ...
City Goers: An Exploration Into Creating Seemingly Intelligent A.I. Systems, 2021 University of Arkansas, Fayetteville
City Goers: An Exploration Into Creating Seemingly Intelligent A.I. Systems, Matthew Brooke
Computer Science and Computer Engineering Undergraduate Honors Theses
Artificial Intelligence systems have come a long way over the years. One particular application of A.I. is its incorporation in video games. A key goal of creating an A.I. system in a video game is to convey a level of intellect to the player. During playtests for Halo: Combat Evolved, the developers at Bungie noticed that players deemed tougher enemies as more intelligent than weaker ones, despite the fact that there were no differences in behavior in the enemies. The tougher enemies provided a greater illusion of intelligence to the players. Inspired by this, I set out to ...
Visual Analysis Of Historical Lessons Learned During Exercises For The United States Air Force Europe (Usafe), 2021 University of Nebraska at Omaha
Visual Analysis Of Historical Lessons Learned During Exercises For The United States Air Force Europe (Usafe), Samantha O'Rourke
Within the United States Air Force, there are repeated patterns of differences observed during exercises. After an exercise is completed, forms are filled out detailing observations, successes, and recommendations seen throughout the exercise. At the most, no two reports are identical and must be analyzed by personnel and then categorized based on common themes observed. Developing a computer application will greatly reduce the time and resources used to analyze each After Action Report. This application can visually represent these observations and optimize the effectiveness of these exercises. The visualization is done through graphs displaying the frequency of observations and recommendations ...
Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, 2021 UA Little Rock Center for Arkansas History and Culture
Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, Elise Tanner, Geoffrey Joseph
Digital Initiatives Symposium
Funded by a National Endowment for Humanities (NEH) Humanities Collections and Reference Resources Foundations Grant, the UA Little Rock Center for Arkansas History and Culture’s “Mapping Renewal” pilot project focused on creating access to and providing spatial context to archival materials related to racial segregation and urban renewal in the city of Little Rock, Arkansas, from 1954-1989. An unplanned interdisciplinary collaboration with the UA Little Rock Arkansas Economic Development Institute (AEDI) has proven to be an invaluable partnership. One team member from each department will demonstrate the Mapping Renewal website and discuss how the collaborative process has changed and ...
Student Academic Conference, 2021 Minnesota State University Moorhead
Student Academic Conference, Caitlin Brooks
Student Academic Conference
No abstract provided.
A Dynamic Programming Approach To Determine Optimum Modularity Level In Industrial Packaging, Marshal Louie, Kumar B
Journal of Applied Packaging Research
Modular packaging facilitate customization for accommodating variable product sizes in a product family. When determining package sizes for product variability, packaging engineers does not find difficulty to determine package dimension for less product variety whereas if the product variety is more, then determining the dimension of modular package involves complex decision-making and time-consuming process to find the optimal solution. This in turn directly impacts the overall lead time of the supply chain. Thus, in this paper a dynamic programming is developed to determine the quantity and dimension of modular packages for every demand of assorted products sizes. The program helps ...
Towards A Complete Formal Semantics Of Rust, 2021 California Polytechnic State University, San Luis Obispo
Towards A Complete Formal Semantics Of Rust, Alexa White
Rust is a relatively new programming language with a unique memory model designed to provide the ease of use of a high-level language as well as the power and control of a low-level language while preserving memory safety. In order to prove the safety and correctness of Rust and to provide analysis tools for its use cases, it is necessary to construct a formal semantics of the language. Existing efforts to construct such a semantic model are limited in their scope and none to date have successfully captured the complete functionality of the language. This thesis focuses on the K-Rust ...
Source Code Comment Classification Artificial Intelligence, 2021 The University of Akron
Source Code Comment Classification Artificial Intelligence, Cole Sutyak
Williams Honors College, Honors Research Projects
Source code comment classification is an important problem for future machine learning solutions. In particular, supervised machine learning solutions that have largely subjective data labels but are difficult to obtain the labels for. Machine learning problems are problems largely because of a lack of data. In machine learning solutions, it is better to have a large amount of mediocre data than it is to have a small amount of good data. While the mediocre data might not produce the best accuracy, it produces the best results because there is much more to learn from the problem.
In this project, data ...
Argumentation Stance Polarity And Intensity Prediction And Its Application For Argumentation Polarization Modeling And Diverse Social Connection Recommendation, 2020 University of Arkansas, Fayetteville
Argumentation Stance Polarity And Intensity Prediction And Its Application For Argumentation Polarization Modeling And Diverse Social Connection Recommendation, Joseph Winstead Sirrianni
Theses and Dissertations
Cyber argumentation platforms implement theoretical argumentation structures that promote higher quality argumentation and allow for informative analysis of the discussions. Dr. Liu’s research group has designed and implemented a unique platform called the Intelligent Cyber Argumentation System (ICAS). ICAS structures its discussions into a weighted cyber argumentation graph, which describes the relationships between the different users, their posts in a discussion, the discussion topic, and the various subtopics in a discussion. This platform is unique as it encodes online discussions into weighted cyber argumentation graphs based on the user’s stances toward one another’s arguments and ideas. The ...
A Bert-Based Dual Embedding Model For Chinese Idiom Prediction, 2020 Singapore Management University
A Bert-Based Dual Embedding Model For Chinese Idiom Prediction, Minghuan Tan, Jing Jiang
Research Collection School Of Computing and Information Systems
Chinese idioms are special fixed phrases usually derived from ancient stories, whose meanings are oftentimes highly idiomatic and non-compositional. The Chinese idiom prediction task is to select the correct idiom from a set of candidate idioms given a context with a blank. We propose a BERT-based dual embedding model to encode the contextual words as well as to learn dual embeddings of the idioms. Specifically, we first match the embedding of each candidate idiom with the hidden representation corresponding to the blank in the context. We then match the embedding of each candidate idiom with the hidden representations of all ...
Actor Concurrency Bugs: A Comprehensive Study On Symptoms, Root Causes, Api Usages, And Differences, 2020 Oakland University
Actor Concurrency Bugs: A Comprehensive Study On Symptoms, Root Causes, Api Usages, And Differences, Mehdi Bagherzadeh, Nicholas Fireman, Anas Shawesh, Raffi T. Khatchadourian
Publications and Research
Actor concurrency is becoming increasingly important in the development of real-world software systems. Although actor concurrency may be less susceptible to some multithreaded concurrency bugs, such as low-level data races and deadlocks, it comes with its own bugs that may be different. However, the fundamental characteristics of actor concurrency bugs, including their symptoms, root causes, API usages, examples, and differences when they come from different sources are still largely unknown. Actor software development can significantly benefit from a comprehensive qualitative and quantitative understanding of these characteristics, which is the focus of this work, to foster better API documentations, development practices ...
Personalized Immunotherapy Treatment Strategies For A System Of Chronic Myelogenous Leukemia, 2020 Tijuana Institute of Technology, Mexico
Personalized Immunotherapy Treatment Strategies For A System Of Chronic Myelogenous Leukemia, Paul Valle
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Cross-Thought For Sentence Encoder Pre-Training, 2020 Singapore Management University
Cross-Thought For Sentence Encoder Pre-Training, Shuohang Wang, Yuwei Fang, Siqi Sun, Zhe Gan, Yu Cheng, Jingjing Liu, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we propose Cross-Thought, a novel approach to pre-training sequence encoder, which is instrumental in building reusable sequence embeddings for large-scale NLP tasks such as question answering. Instead of using the original signals of full sentences, we train a Transformer-based sequence encoder over a large set of short sequences, which allows the model to automatically select the most useful information for predicting masked words. Experiments on question answering and textual entailment tasks demonstrate that our pre-trained encoder can outperform state-of-the-art encoders trained with continuous sentence signals as well as traditional masked language modeling baselines. Our proposed approach also ...
Evaluating Performance Of Openmp Tasks In A Seismic Stencil Application, 2020 Stony Brook University
Evaluating Performance Of Openmp Tasks In A Seismic Stencil Application, Eric Raut, Jie Meng, Mauricio Araya-Polo, Barbara Chapman
Department of Applied Mathematics & Statistics Faculty Publications
Simulations based on stencil computations (widely used in geosciences) have been dominated by the MPI+OpenMP programming model paradigm. Little effort has been devoted to experimenting with task-based parallelism in this context. We address this by introducing OpenMP task parallelism into the kernel of an industrial seismic modeling code, Minimod. We observe that even for these highly regular stencil computations, taskified kernels are competitive with traditional OpenMP-augmented loops, and in some experiments tasks even outperform loop parallelism.
This promising result sets the stage for more complex computational patterns. Simulations involve more than just the stencil calculation: a collection of kernels ...
A Fortran-Keras Deep Learning Bridge For Scientific Computing, 2020 University of California, Irvine
A Fortran-Keras Deep Learning Bridge For Scientific Computing, Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi
Engineering Faculty Articles and Research
Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way ...
Visualocv: Refined Dataflow Programming Interface For Opencv, 2020 Southern Adventist University
Visualocv: Refined Dataflow Programming Interface For Opencv, John Boggess
MS in Computer Science Project Reports
OpenCV is a popular tool for developing computer vision algorithms; however, prototyping OpenCV-based algorithms is a time consuming and iterative process. VisualOCV is an open source tool to help users better understand and create computer vision algorithms. A user can see how data is processed at each step in their algorithm, and the results of any changes to the algorithm will be displayed to the user immediately. This can allow the user to easily experiment with various computer vision methods and their parameters. EyeCalc 1.0 uses the Microsoft Foundation Class Library, an old GUI framework by Microsoft, and contains ...
Modified Surrogate Cutting Plane Algorithm (Mscpa) For Integer Linear Programming Problems, 2020 University of Technology, Iraq
Modified Surrogate Cutting Plane Algorithm (Mscpa) For Integer Linear Programming Problems, Israa Hasan
Emirates Journal for Engineering Research
This work concerned with introducing a new algorithm for solving integer linear programming problems. The improved algorithm can help by decreasing a calculation the complexity of these problems, an advantages of the proposed method are to reduce the solution time and to decrease algorithmic complexity. Some specific numerical examples are discussed to demonstrate the validity and applicability of the proposed method. The numerical results are compared with the solution of integer linear programming problems by using cutting plane method (Gomory method).
Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, 2020 CUNY Hunter College
Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus
School of Arts & Sciences Theses
This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass ...