Physical Sciences and Mathematics Commons^™

Action Selection For Composable Modular Deep Reinforcement Learning, Vaibhav Gupta, Daksh Anand, Praveen Parachuri, Akshat Kumar

Research Collection School Of Computing and Information Systems

In modular reinforcement learning (MRL), a complex decision making problem is decomposed into multiple simpler subproblems each solved by a separate module. Often, these subproblems have conflicting goals, and incomparable reward scales. A composable decision making architecture requires that even the modules authored separately with possibly misaligned reward scales can be combined coherently. An arbitrator should consider different module’s action preferences to learn effective global action selection. We present a novel framework called GRACIAS that assigns fine-grained importance to the different modules based on their relevance in a given state, and enables composable decision making based on modern deep RL …

A Novel Dynamic Analysis Infrastructure To Instrument Untrusted Execution Flow Across User-Kernel Spaces, Jiaqi Hong, Xuhua Ding

Research Collection School Of Computing and Information Systems

Code instrumentation and hardware based event trapping are two primary approaches used in dynamic malware analysis systems. In this paper, we propose a new approach called Execution Flow Instrumentation (EFI) where the analyzer execution flow is interleaved with the target flow in user- and kernel-mode, at junctures flexibly chosen by the analyzer at runtime. We also propose OASIS as the system infrastructure to realize EFI with virtues of the current two approaches, however without their drawbacks. Despite being securely and transparently isolated from the target, the analyzer introspects and controls it in the same native way as instrumentation code. We …

Characterising The Knowledge About Primitive Variables In Java Code Comments, Mahfouth Alghamdi, Shinpei Hayashi, Takashi Kobayashi, Christoph Treude

Research Collection School Of Computing and Information Systems

Primitive types are fundamental components available in any programming language, which serve as the building blocks of data manipulation. Understanding the role of these types in source code is essential to write software. Little work has been conducted on how often these variables are documented in code comments and what types of knowledge the comments provide about variables of primitive types. In this paper, we present an approach for detecting primitive variables and their description in comments using lexical matching and advanced matching. We evaluate our approaches by comparing the lexical and advanced matching performance in terms of recall, precision, …

How Do Software Developers Use Github Actions To Automate Their Workflows?, Timothy Kinsman, Mairieli Wessel, Marco Gerosa, Christoph Treude

Research Collection School Of Computing and Information Systems

Automated tools are frequently used in social coding repositories to perform repetitive activities that are part of the distributed software development process. Recently, GitHub introduced GitHub Actions, a feature providing automated work-flows for repository maintainers. Although several Actions have been built and used by practitioners, relatively little has been done to evaluate them. Understanding and anticipating the effects of adopting such kind of technology is important for planning and management. Our research is the first to investigate how developers use Actions and how several activity indicators change after their adoption. Our results indicate that, although only a small subset of …

Research Artifact: The Potential Of Meta-Maintenance On Github, Hideaki Hata, Raula Kula, Takashi Ishio, Christoph Treude

Research Collection School Of Computing and Information Systems

This is a research artifact for the paper “Same File, Different Changes: The Potential of Meta-Maintenance on GitHub”. This artifact is a data repository including a list of studied 32,007 repositories on GitHub, a list of targeted 401,610,677 files, the results of the qualitative analysis for RQ2, RQ3, and RQ4, the results of the quantitative analysis for RQ5, and survey material for RQ6. The purpose of this artifact is enabling researchers to replicate our mixed-methods results of the paper, and to reuse the results of our exploratory study for further software engineering research. This research artifact is available at https://github.com/NAIST-SE/MetaMaintenancePotential …

Same File, Different Changes: The Potential Of Meta-Maintenance On Github, Hideaki Hata, Raula Kula, Takashi Ishio, Christoph Treude

Research Collection School Of Computing and Information Systems

Online collaboration platforms such as GitHub have provided software developers with the ability to easily reuse and share code between repositories. With clone-and-own and forking becoming prevalent, maintaining these shared files is important, especially for keeping the most up-to-date version of reused code. Different to related work, we propose the concept of meta-maintenance-i.e., tracking how the same files evolve in different repositories with the aim to provide useful maintenance opportunities to those files. We conduct an exploratory study by analyzing repositories from seven different programming languages to explore the potential of meta-maintenance. Our results indicate that a majority of active …

Tensor Low-Rank Representation For Data Recovery And Clustering, Pan Zhou, Canyi Lu, Jiashi Feng, Zhouchen Lin, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Multi-way or tensor data analysis has attracted increasing attention recently, with many important applications in practice. This article develops a tensor low-rank representation (TLRR) method, which is the first approach that can exactly recover the clean data of intrinsic low-rank structure and accurately cluster them as well, with provable performance guarantees. In particular, for tensor data with arbitrary sparse corruptions, TLRR can exactly recover the clean data under mild conditions; meanwhile TLRR can exactly verify their true origin tensor subspaces and hence cluster them accurately. TLRR objective function can be optimized via efficient convex programing with convergence guarantees. Besides, we …

Silver Bow Creek/Butte Area Npl Site Butte Priority Soils Operable Unit, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Silver Bow Creek/Butte Area Npl Site Butte Priority Soils Operable Unit, Atlantic Richfield Company

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit Preliminary (30%) Design Butte Reduction Works Smelter Area Remedial Action Construction Drawings, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Teachability And Interpretability In Reinforcement Learning, Jeevan Rajagopal

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

There have been many recent advancements in the field of reinforcement learning, starting from the Deep Q Network playing various Atari 2600 games all the way to Google Deempind's Alphastar playing competitively in the game StarCraft. However, as the field challenges more complex environments, the current methods of training models and understanding their decision making become less effective. Currently, the problem is partially dealt with by simply adding more resources, but the need for a better solution remains.

This thesis proposes a reinforcement learning framework where a teacher or entity with domain knowledge of the task to complete can assist …

Association Between Dietary Inflammatory Index, Dietary Patterns, Plant-Based Dietary Index And The Risk Of Obesity, Yoko B. Wang, Nitin Shivappa, James R. Hébert Scd, Amanda J. Page, Yohannes Adama Melaku

Faculty Publications

Evidence on the association between various dietary constructs and obesity risk is limited. This study aims to investigate the longitudinal relationship between different diet indices and dietary patterns with the risk of obesity. Non-obese participants (n = 787) in the North West Adelaide Health Study were followed from 2010 to 2015. The dietary inflammatory index (DII®), plant-based dietary index (PDI) and factor-derived dietary pattern scores were computed based on food frequency questionnaire data. We found the incidence of obesity was 7.62% at the 5-year follow up. In the adjusted model, results from multivariable log-binomial logistic regression showed that a prudent …

Development Of High Throughput Assays For Identification And Evaluation Of Small Molecule Inhibitors Of Microrna-31 Expression, Jackline A. Onyango

Masters Theses

Dysregulated expression of miRNAs has been linked to numerous cancers. On the other hand, miRNAs are potential drug targets due to the ability of their precursor molecules to fold into ligand binding structures. Small-molecule modulators of miRNAs offers opportunity for the development of new therapeutic agents and tools to further probe the mechanisms of miRNA functions. To facilitate the identification of miRNA modulators, the appropriate screening systems are needed, which would be adaptable for high-throughput applications, and allow for quantitative measurements. In this text, we present a molecular beacon-based assay to identify molecules that inhibit miRNA-31 processing by Dicer and …

A Process For Adm-300 Radiation Detector Modernization For Military Applications, Caesar R. Pereira

UNLV Theses, Dissertations, Professional Papers, and Capstones

An investigation to re-evaluate the current use in military applications of the ADM-300 Multi-Functional Survey Instrument and its requirements are provided. This paper outlines a method to upgrade the ADM-300 due to its eventual obsolescence using newly developed requirements that meet the original justification for use in the USAF in 1992. The capabilities and features of various detectors are analyzed and compared to the ADM-300. Response curves are generated using Monte Carlo simulations. The detectors are prioritized based on their performance to create metrics. A metanalysis of the metrics is conducted to limit bias within the process and justify their …

Brave New World Reboot: Technology’S Role In Consumer Manipulation And Implications For Privacy And Transparency, Allie Mertensotto

Marketing Undergraduate Honors Theses

Most consumers are aware that our data is being obtained and collected through the use of our devices we keep in our homes or even on our person throughout the day. But, it is understated how much data is being collected. Conversations you have with your peers – in a close proximity of a device – are being used to tailor advertising. The advertisements you receive on your devices are uniquely catered to your individual person, due to the fact it consistently uses our data to produce efficient and personal ads. On the flip side, our government is also tapping …

The Bridge To Closing The Green Gap, Samantha Rife

Marketing Undergraduate Honors Theses

In today’s society, we have seen the theme of green consciousness and sustainability become more prevalent as the years pass by. Even as this concept seems to increase in consumer engagement there is not a proportional increase in consumer behavior. This is what is referred to as the gap between green consciousness and green consumerism. Many believe the root of this issue can be solved by increasing regulations. However, I believe this gap can be narrowed by using brands to shift consumers behaviors through their message. The main question that I want to focus in on is, “Can a brand …

Technology And Sustainability: The New Business Playing Field, Havovi Joshi

Asian Management Insights

Two topics that have consistently cropped up in conversations among business leaders during the pandemic are technology, in the context of the pervasiveness and quickening pace of digital transformation, and sustainability, especially how we should be doing business without harming the environment and society. The collective belief is that both topics will continue to rise on the world’s agenda, reshaping entire industries while creating new ones. They have changed the way of doing business. So what does the new playbook look like?

A Novel Mra-Based Framework For Segmenting The Cerebrovascular System And Correlating Cerebral Vascular Changes To Mean Arterial Pressure, Fatma Taher, Heba Kandil, Yitzhak Gebru, Ali Mahmoud, Ahmed Shalaby, Shady El‐Mashad, Ayman El‐Baz

All Works

Blood pressure (BP) changes with age are widespread, and systemic high blood pressure (HBP) is a serious factor in developing strokes and cognitive impairment. A non‐invasive methodology to detect changes in human brain’s vasculature using Magnetic Resonance Angiography (MRA) data and correlation of cerebrovascular changes to mean arterial pressure (MAP) is pre-sented. MRA data and systemic blood pressure measurements were gathered from patients (n = 15, M = 8, F = 7, Age = 49.2 ± 7.3 years) over 700 days (an initial visit and then a follow‐up period of 2 years with a final visit.). A novel segmentation algorithm …

Study Of Neutral Hadron Production In A High Intensity Particle Physics Experiment., Jake W. Berg

Electronic Theses and Dissertations

In this dissertation I present independent measurements of the multiplicities, R, of π⁰ and η mesons produced in annihilation interactions of electrons and positrons at a center-of-mass energy of 10.54 GeV. Data were collected using the BaBar detector at the PEP-II storage rings located at the SLAC National Accelerator Laboratory in Menlo Park, California. Both mesons have a decay mode to two photons, which is used to identify them and measure their production per event. I find R(π⁰) = 2.8±0.3 per event and R(η) = 0.25±0.03 per event. I also present my contributions to …

Observing Changes In Vegetable Production Through Alternative Agricultural Practices, Austin Grey Livingston

MSU Graduate Theses

Locally, responsibly grown produce is becoming more popular as consumers are shifting to organic products or those obtained at a local farmer’s market. The importance of soil health through conservation practices is increasing as the negative effects of industrial production are apparent. The over-application of synthetic fertilizers, soil erosion from wind and water, and nutrient leaching in high vegetable production areas has initiated a need for the investigation of alternative management practices. The main objective of this study is to evaluate the effects of tillage and cover crops in the production of green beans and okra. In 2019 and 2020, …

An Analysis Of Modern Password Manager Security And Usage On Desktop And Mobile Devices, Timothy Oesch

Doctoral Dissertations

Security experts recommend password managers to help users generate, store, and enter strong, unique passwords. Prior research confirms that managers do help users move towards these objectives, but it also identified usability and security issues that had the potential to leak user data or prevent users from making full use of their manager. In this dissertation, I set out to measure to what extent modern managers have addressed these security issues on both desktop and mobile environments. Additionally, I have interviewed individuals to understand their password management behavior.

I begin my analysis by conducting the first security evaluation of the …

Learning Hierarchical Traversability Representation For Efficient Multi-Resolution Path Planning, Reza Etemadi Idgahi

Computer Science and Engineering Theses

Path finding on grid-based obstacle maps is an important and much studied problem with applications in robotics and autonomy. Traditionally, in the AI community, heuristic search methods (e.g. based on Dijkstra and A*, or based on random trees) are used to solve this problem. This search, however incurs significant computational cost that grows with the size and resolution of the obstacle grid and has to be mitigated with effective heuristics in order to allow path finding in real time. In this work we introduce a learning framework using deep neural networks with a stackable convolution kernel to establish a hierarchy …

Machine Learning With Graphs, Jianjin Deng

Computer Science and Engineering Dissertations

In recent years, graph-based machine learning methods have attracted great attention because of their effectiveness and efficiency. Inspired by this trend, this thesis summarizes my research topics on machine learning techniques for the purpose of handling various kinds of problems on large graph data. Generally, this thesis contains two parts. The first part is devoted to graph embedding, which aims to encode graph structure into dense vectors (or embeddings). In particular, we will consider a low rank-matrix factorization based approach to learn embeddings of attributed graphs. By jointly preserving graph structure and attribute-level similarity, our approach can generate embeddings, whose …

Structure Aware Human Pose Estimation Using Adversarial Learning, Suryam Sharma

Computer Science and Engineering Theses

Pose estimation using Deep Neural Networks (DNNs) has shown outstanding performance in recent years, due to the availability of powerful GPUs and larger training datasets. However, there are still many challenges due to the large variability of human body appearances, lighting conditions, complex background, occlusions and postures. Among all these peculiarities, partial occlusions, and overlapping body poses often result in deviated pose predictions. These circumstances can result in wrong and sometimes unrealistic results. The human mind can predict such poses because of the underlying structural awareness of the geometry, of a human body. In this thesis, we discuss an efficient …

Low-Dose Ct Image Denoising Using Deep Learning Methods, Zeheng Li

Computer Science and Engineering Theses

Low-dose computed tomography (LDCT) has raised highly attention since the counterpart, full-dose computed tomography (FDCT), brings potential ionizing radiation influence to patients. However, LDCT still suffers from several issues such as relatively higher noise level, which limits its uses in practical applications. To improve LDCT image quality, conventional denoising methods, such as KSVD and BM3D, are first introduced to suppress noise in low-dose images. These methods, however, works under assumptions that are not robust to various data. In this paper, we conduct an extensive research on deep learning based denoising method in LDCT images. We mainly base on Generative-Adversarial Network …

Using Sentiment And Emotion Analysis Of News Articles To Analyze The Effects Of Leader’S Statements On Covid-19 Spread, Poojitha Thota

Computer Science and Engineering Theses

Leaders generally include government officials, politicians, etc. Their statements can highly affect people’s decisions in many ways. Currently, in the pandemic situation, many statements were being passed every hour and day, which showed an impact on the spread of corona virus cases at certain location. So, this paper proposes a supervised model to analyze the variations of COVID-19 data based upon the leader’s statements passed at certain time and location. The proposed methodology consists of sentiment and emotion analysis for the leader’s statements to determine the true intentions of the leader. The leader’s statements are a collection of data obtained …

Predict Behavioural Scores In Sleep Apnea Patients From Resting State Near-Infrared Spectroscopy (Fnirs), Amnah Abdelrahman

Computer Science and Engineering Theses

Sleep disorders are common among adults and children; it has serious consequences on their heath, cognitive development and quality of life. However, some sleep disorders are challenging to diagnose and more challenging to treat. Practitioners often rely on AIH for OSA patients’ classification task, where considering one measurement could raise a risk of oversimplification. Studies show the correlation between sleep disorders, specifically OSA, and mental health. On the other side there are an increasing number of studies suggested evidence of a relationship between the dynamic properties of functional brain structure with the behaviors and cognition attributes. This novel work objective …

End-User Framework For Robot Control, Kaustubh Kedar Rajpathak

Computer Science and Engineering Theses

This thesis describes in detail a developed end-user framework for a humanrobot collaborative system for common tasks, such as pick and place. The system is designed for semi-automated pick and place tasks as well as manual operation making it flexible for multiple use-case scenarios. The goal of the system is to make the robotic system multi-functional, easy to use with a graphical user interface and should perform common tasks with the help of a human teammate. Integration with object recognition neural networks (YOLOv3) and an RGB-Depth camera help automate pick and place tasks with a wide variety of objects.

Human Factors Analysis And Monitoring To Enhance Human-Robot Collaboration, Akilesh Rajavenkatanarayanan

Computer Science and Engineering Dissertations

Human-Machine Interaction (HMI) can be defined as a way for us to communicate with machines through user interfaces. User interfaces have evolved from complicated punch cards and levers in the first analog computers to a more natural way of interaction using speech or gestures in today's digital assistants. Technological advancements in computing devices have paved the way for smart, powerful computers to be part of our everyday lives. There is also an increasing trend of using smart computing devices and robots in manufacturing lines, medical procedures, rehabilitation, and personal care. The umbrella of HMI typically covers several areas like Human-Robot …

Glaze Epochs: Externalizing Material Knowledge Through Tangible Data Records In A Ceramics Studio, Hedieh Moradi

Computer Science and Engineering Theses

The "material turn" in HCI has placed a renewed focus on informing design from the relationships found in material-based interactions. While several ethnographic works provide insight into how practitioners converse with materials, it is less understood how these conversations transform into a skilled practitioner's mental model. I examine the material practice of glazing that gives ceramics its decorative and functional characteristics and involves fusing mixtures of silica, alumina, and flux onto a clay body through kiln firing. This practice evolves over decades, developing from multiple trajectories, including theoretical foundations, systematic experimentation, and happy accidents. This work describes virtual site visits …