Computer Sciences Commons^™

Long Term Predictive Modeling On Big Spatio-Temporal Data, Yong Zhuang

Graduate Doctoral Dissertations

In the era of massive data, one of the most promising research fields involves the analysis of large-scale Spatio-temporal databases to discover exciting and previously unknown but potentially useful patterns from data collected over time and space. A modeling process in this domain must take temporal and spatial correlations into account, but with the dimensionality of the time and space measurements increasing, the number of elements potentially contributing to a target sharply grows, making the target's long-term behavior highly complex, chaotic, highly dynamic, and hard to predict. Therefore, two different considerations are taken into account in this work: one is …

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …

Mitigating The Spread Of Measles Under Constrained Health Care Resources In Tanzania Using Social Contact Network Models, Herieth Rwezaura, Seán Mcgarraghy

Tanzania Journal of Science

Tanzania revaccinates individuals during measles outbreaks, despite having scant healthcare resources. We construct epidemiological models of measles spread by employing a hybrid of existing social contact networks models to develop SEIR simulation model. Using demographic and measles surveillance data from three rural villages in Tanzania, we simulate the spread of measles and examine which vaccination strategies can effectively control outbreaks. Results strongly indicate the spread of measles largely depends on contact rates among infected individuals within a population. Findings indicate a need for targeted vaccination for children of 6 months to 15 years of age, but equally for unvaccinated older …

A Novel Arabic Corpus For Text Classification Using Deep Learning And Word Embedding, Roua A. Abou Khachfeh, Islam El Kabani, Ziad Osman

BAU Journal - Science and Technology

Over the last years, Natural Language Processing (NLP) for Arabic language has obtained increasing importance due to the massive textual information available online in an unstructured text format, and its capability in facilitating and making information retrieval easier. One of the widely used NLP task is “Text Classification”. Its goal is to employ machine learning technics to automatically classify the text documents into one or more predefined categories. An important step in machine learning is to find suitable and large data for training and testing an algorithm. Moreover, Deep Learning (DL), the trending machine learning research, requires a lot of …

Evaluating Technology-Mediated Collaborative Workflows For Telehealth, Christopher Bondy Ph.D., Pengcheng Shi, Pamela Grover Md, Vicki Hanson, Linlin Chen, Rui Li

Articles

Goals: This paper discusses the need for a predictable method to evaluate gains and gaps of collaborative technology-mediated workflows and introduces an evaluation framework to address this need. Methods: The Collaborative Space Analysis Framework (CS-AF), introduced in this research, is a cross-disciplinary evaluation method designed to evaluate technology-mediated collaborative workflows. The 5-step CS-AF approach includes: (1) current-state workflow definition, (2) current-state (baseline) workflow assessment, (3) technology-mediated workflow development and deployment, (4) technology-mediated workflow assessment, (5) analysis, and conclusions. For this research, a comprehensive, empirical study of hypertension exam workflow for telehealth was conducted using the CS-AF approach. Results: The CS-AF …

A Framework Of Web-Based Dark Patterns That Can Be Detected Manually Or Automatically, Ioannis Stavrakakis, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney

Articles

This research explores the design and development of a framework for the detection of Dark Patterns, which are a series of user interface tricks that manipulate users into actions that they do not intend to do, for example, share more data than they want to, or spend more money than they plan to. The interface does this using either deception or other psychological nudges. User Interface experts have categorized a number of these tricks that are commonly used and have called them Dark Patterns. They are typically varied in their form and what they do, and the goal of this …

On The Documentation Of Refactoring Types, Eman Abdullah Alomar, Jiaqian Liu, Kenneth Addo, Mohamed Wiem Mkaouer, Christian D. Newman, Ali Ouni, Zhe Yu

Articles

Commit messages are the atomic level of software documentation. They provide a natural language description of the code change and its purpose. Messages are critical for software maintenance and program comprehension. Unlike documenting feature updates and bug fixes, little is known about how developers document their refactoring activities. Specifically, developers can perform multiple refactoring operations, including moving methods, extracting classes, renaming attributes, for various reasons, such as improving software quality, managing technical debt, and removing defects. Yet, there is no systematic study that analyzes the extent to which the documentation of refactoring accurately describes the refactoring operations performed at the …

What Interactive Web Features Are Most Used, Travis Tyler

Experiential Learning Projects

The use of interactive features in websites has become common place on the internet. People use these tools to help navigate and understand the content related to that website. However, due the large variety of websites it can be tricky to understand what features are best to utilize based on the topic of your site. This paper seeks to address this issue by researching how users interact and utilized different features on different websites. Research is gathered via scholarly articles and direct data gathered from volunteers. This data shows users tend to favor more interactive tools to help with navigation, …

Workflow Critical Path: A Data-Oriented Critical Path Metric For Holistic Hpc Workflows, Daniel D. Nguyen, Karen L. Karavanic

Computer Science Faculty Publications and Presentations

Current trends in HPC, such as the push to exascale, convergence with Big Data, and growing complexity of HPC applications, have created gaps that traditional performance tools do not cover. One example is Holistic HPC Workflows — HPC workflows comprising multiple codes, paradigms, or platforms that are not developed using a workflow management system. To diagnose the performance of these applications, we define a new metric called Workflow Critical Path (WCP), a data-oriented metric for Holistic HPC Workflows. WCP constructs graphs that span across the workflow codes and platforms, using data states as vertices and data mutations as edges. …

Explaining Deep Learning Models For Tabular Data Using Layer-Wise Relevance Propagation, Ihsan Ullah, Andre Rios, Vaibhov Gala, Susan Mckeever

Articles

Trust and credibility in machine learning models are bolstered by the ability of a model to explain its decisions. While explainability of deep learning models is a well-known challenge, a further challenge is clarity of the explanation itself for relevant stakeholders of the model. Layer-wise Relevance Propagation (LRP), an established explainability technique developed for deep models in computer vision, provides intuitive human-readable heat maps of input images. We present the novel application of LRP with tabular datasets containing mixed data (categorical and numerical) using a deep neural network (1D-CNN), for Credit Card Fraud detection and Telecom Customer Churn prediction use …

Evaluation Of Gpu Acceleration For Wrf–Sfire, Joshua Benz

Master's Projects

WRF–SFIRE is an open source, atmospheric–wildfire model that couples the WRF model with the level set fire spread model to simulate wildfires in real time. This model has many applications and more scientific questions can be asked and answered if the model can be run faster. Nvidia has put a lot of effort into easing the barrier of entry for accelerating applications with their tools to be run on GPUs. Various physical simulations have been successfully ported to utilize GPUs and have benefited from the speed increase. In this research, we take a look at WRF-SFIRE and try to use …

Seedemu: The Seed Internet Emulator, Honghao Zeng

Theses - ALL

I studied and experimented with the idea of building an emulator for the Internet. While there are various already available options for such a task, none of them takes the emulation of the entire Internet as an important feature in mind. Those emulators and simulators can handle small-scale networks pretty well, but lacks the ability to handle large-size networks, mainly due to:

- Not being able to run many nodes, or requires very powerful hardware to do so,- Lacks convenient ways to build a large emulation, and - Lacks reusability: once something is built, it is very hard to re-use …

Winter 2021

In The Loop

2021 Emmy Nominees; Animator Tapped by Cartoon Network; IndieCade Horizons 2021; Hack4Space; Security Daemons Prevail; Role Models: DePaul Originals Game Studio students build industry-level skills that benefit themselves and others; Frames and Fortune: Eugene Bush programmed his indie video studio with patience and planning; Reality Check: Heather Snyder Quinn augments reality to question systems of unchecked power

Adopting Agility In Academia Through Pilot Projects, Omar Ochoa, Massood Towhidnejad

Papers

This innovate practice work in progress paper presents our initial findings about the application of agile process in the day to day operation of an academic department. The benefits of agile methods, which are processes that are lightweight and people-oriented, are well-known. Agile methods provide the ability to respond faster to the changing needs of stakeholders, improved product quality, team over individual goals, and better transparency. Therefore, one would expect adaption of the agile process within academic environment would be welcomed, however, unique issues exist within faculty that impact adoption; faculty have different goals that change through their tenure, and …

Twin Anomaly Detection System, Paaras Chand

Master's Projects

Anomaly detection performs well in situations where signature (and other rule-based) methods fail; there is no need to identify every threat as long as it is different from the norm. The tradeoff is that anomaly detection often results in a large number of false positives. While previous work has capitalized on the data imbalance problem to train models with only one set of data (one-class classification), few have utilized the limiting set for anything other than testing purposes. This paper seeks to utilize two anomaly detectors: one that is trained on the positive set and one that is trained on …

A Hybrid Machine Learning Framework For Predicting Students’ Performance In Virtual Learning Environment, Edmund Evangelista

All Works

Virtual Learning Environments (VLE), such as Moodle and Blackboard, store vast data to help identify students' performance and engagement. As a result, researchers have been focusing their efforts on assisting educational institutions in providing machine learning models to predict at-risk students and improve their performance. However, it requires an efficient approach to construct a model that can ultimately provide accurate predictions. Consequently, this study proposes a hybrid machine learning framework to predict students' performance using eight classification algorithms and three ensemble methods (Bagging, Boosting, Voting) to determine the best-performing predictive model. In addition, this study used filter-based and wrapper-based feature …

Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao

Posters-at-the-Capitol

Gaze tracking has become an established technology that enables using an individual’s gaze as an input signal to support a variety of applications in the context of Human-Computer Interaction. Gaze tracking primarily relies on sensing devices such as infrared (IR) cameras. Nevertheless, in the recent years, several attempts have been realized at detecting gaze by acquiring and processing images acquired from standard RGB cameras. Nowadays, there are only a few publicly available open-source libraries and they have not been tested extensively. In this paper, we present the result of a comparative analysis that studied a commercial eye-tracking device using IR …

Teaching Computer Science Csc 222, Harrison Dekker

Library Impact Statements

No abstract provided.

Development Experience Of International Open Source And Its Enlightenment To Construction Of Open Source Innovation System In China, Yuntao Long, Xiaoming Wang, Rong Gu, Yungang Bao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Open source has become an essential innovation model for global technological progress and the construction of an open source innovation system is an important path for China to achieve self-reliance and self-improvement in science and technology. As an indispensable part of the global software value chain and high-tech industry chain, China needs to improve its open source innovation ecosystem. The paper, based on a systematic review of the related development policies and successful experiences on the open source work in US and Europe, puts forward a series of policy suggestions to solve the practical problems faced by the construction of …

Sufficient Condition For The Possibility Of Completing The Pursuit, Nodirbek Umrzaqov

Scientific Bulletin. Physical and Mathematical Research

In this paper, the problem of chase is represented by a system of linear differential equations of motion dynamics. In this case, there is an integral limit to the control parameter of the evader, and a geometric limit to the control parameter of the pursuer. The pursuer is allowed to use the control that the fugitive has used so far to build his control. There are enough conditions for the game to end even if it starts from any starting point. An algorithm for constructing the control function of the pursuer is defined. It should also be noted that the …

Computational Thinking For Teachers, Susan Imberman

Open Educational Resources

This is a syllabus for a course in computational thinking. The course described introduces preservice and inservice teachers to the fundamental concepts of computer science, including web design, coding, ethics, computational thinking, course resources, etc.

Task Classification During Visual Search Using Classic Machine Learning And Deep Learning, Devangi Vilas Chinchankar

Master's Projects

In an average human life, the eyes not only passively scan visual scenes, but most times end up actively performing tasks including, but not limited to, searching, comparing, and counting. As a result of the advances in technology, we are observing a boost in the average screen time. Humans are now looking at an increasing number of screens and in turn images and videos. Understanding what scene a user is looking at and what type of visual task is being performed can be useful in developing intelligent user interfaces, and in virtual reality and augmented reality devices. In this research, …

Nitrogenase Iron Protein Classification Using Cnn Neural Network, Amer Rez

Master's Projects

The nitrogenase iron protein (NifH) is extensively used to study nitrogen fixation, the ecologically vital process of reducing atmospheric nitrogen to a bioavailable form. The discovery rate of novel NifH sequences is high, and there is an ongoing need for software tools to mine NifH records from the GenBank repository. Since record annotations are unreliable, because they contain errors, classifiers based on sequence alone are required. The ARBitrator classifier is highly successful but must be initialized by extensive manual effort. A Deep Learning approach could substantially reduce manual intervention. However, attempts to build a character-based Deep Learning NifH classifier were …

Dynamic Resource Management Of Fog-Cloud Computing For Iot Support, Mariia Surmenok

Master's Projects

The internet of things (IoT) is an integrated part of contemporary life. It includes wearable devices, such as smart watches and cell phones, as well as sensors for Smart City. Fog computing can improve the efficiency and battery life of IoT devices by offloading tasks to fog cloud. It is important to have fog clusters near the IoT device for faster data offload. The goal of this project is to develop dynamic resource allocation for on-demand fog computing cluster to efficiently deploy tasks from IoT. This report studies the different research papers about the current state of resource management in …

Achieving Fairness Through Load-Balancing In Social Cloud Computing Networks, Kaiyi Huang

Master's Projects

Cloud-based computing networks have taken over the digital landscape. From small non-profits to large multinational corporations, more and more entities have been offloading computing effort to the cloud in order to take advantage of the increased cost-efficiency and scalability of cloud computing. One of the new types of cloud that have emerged is the P2P cloud, which disengages from a traditional datacenter setup by allowing users to instead share their own computing hardware into a cloud to take advantage of cloud computing’s advantages at an even lower cost. However, this new paradigm comes with a slew of challenges, notably, security …

The Impact Of Programming Language’S Type On Probabilistic Machine Learning Models, Sherif Elsaid

Master's Projects

Software development is an expensive and difficult process. Mistakes can be easily made, and without extensive review process, those mistakes can make it to the production code and may have unintended disastrous consequences.

This is why various automated code review services have arisen in the recent years. From AWS’s CodeGuro and Microsoft’s Code Analysis to more integrated code assistants, like IntelliCode and auto completion tools. All of which are designed to help and assist the developers with their work and help catch overlooked bugs.

Thanks to recent advances in machine learning, these services have grown tremen- dously in sophistication to …

Privacy Preserving For Multiple Computer Vision Tasks, Amala Varghese Wilson

Master's Projects

Privacy-preserving visual recognition is an important area of research that is gaining momentum in the field of computer vision. In a production environment, it is critical to have neural network models learn continually from user data. However, sharing raw user data with a server is less desirable from a regulatory, security and privacy perspective. Federated learning addresses the problem of privacy- preserving visual recognition. More specifically, we closely examine and dissect a framework known as Dual User Adaptation (DUA) presented by Lange et al. at CVPR 2020, due to its novel idea of bringing about user-adaptation on both the server-side …

Predicting Stocks With Lstm-Based Drnn And Gan, Duy Ngo

Master's Projects

Trading equities can be very lucrative for some and a gamble for others. Professional traders and retail traders are constantly amassing information to be a step ahead of the market to profit off the value of stocks on the market. Some of the tools in their arsenal include different types of calculations based on a variety of data collected on a stock. Technical analysis is a technique for traders to analyze the data of equities presented on charts. Often, the way the price changes over time can be used as an indicator for traders to predict how future prices will …

An Open Source Direct Messaging And Enhanced Recommendation System For Yioop, Aniruddha Dinesh Mallya

Master's Projects

Recommendation systems and direct messaging systems are two popular components of web portals. A recommendation system is an information filtering system that seeks to predict the "rating" or "preference" a user would give to an item and a direct messaging system allows private communication between users of any platform. Yioop, is an open source, PHP search engine and web portal that can be configured to allow users to create discussion groups, blogs, wikis etc.

In this project, we expanded on Yioop’s group system so that every user now has a personal group. Personal groups were then used to add user …

Robotic Olfactory-Based Navigation With Mobile Robots, Lingxiao Wang

Doctoral Dissertations and Master's Theses

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. It has been viewed as challenging due to the turbulent nature of airflows and the resulting odor plume characteristics. The key to correctly finding an odor source is designing an effective olfactory-based navigation algorithm, which guides the robot to detect emitted odor plumes as cues in finding the source. This dissertation proposes three kinds of olfactory-based navigation methods to improve search efficiency while maintaining a low computational cost, incorporating different machine learning and artificial intelligence methods.

A. …