Physical Sciences and Mathematics Commons^™

From Asset Flow To Status, Action And Intention Discovery: Early Malice Detection In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu

Research Collection School Of Computing and Information Systems

Cryptocurrency has been subject to illicit activities probably more often than traditional financial assets due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all three critical properties of early detection, good interpretability, and versatility for various illicit activities. However, existing solutions cannot meet all these requirements, as most of them heavily rely on deep learning without interpretability and are only available for retrospective analysis of a specific illicit type. To tackle all these challenges, we propose Intention Monitor for early malice detection in Bitcoin, where the on-chain record data for a certain …

Mitigating Membership Inference Attacks Via Weighted Smoothing, Minghan Tan, Xiaofei Xie, Jun Sun, Tianhao Wang

Research Collection School Of Computing and Information Systems

Recent advancements in deep learning have spotlighted a crucial privacy vulnerability to membership inference attack (MIA), where adversaries can determine if specific data was present in a training set, thus potentially revealing sensitive information. In this paper, we introduce a technique, weighted smoothing (WS), to mitigate MIA risks. Our approach is anchored on the observation that training samples differ in their vulnerability to MIA, primarily based on their distance to clusters of similar samples. The intuition is clusters will make model predictions more confident and increase MIA risks. Thus WS strategically introduces noise to training samples, depending on whether they …

Transformer-Based Multi-Task Learning For Crisis Actionability Extraction, Yuhao Zhang, Siaw Ling Lo, Phyo Yi Win Myint

Research Collection School Of Computing and Information Systems

Social media has become a valuable information source for crisis informatics. While various methods were proposed to extract relevant information during a crisis, their adoption by field practitioners remains low. In recent fieldwork, actionable information was identified as the primary information need for crisis responders and a key component in bridging the significant gap in existing crisis management tools. In this paper, we proposed a Crisis Actionability Extraction System for filtering, classification, phrase extraction, severity estimation, localization, and aggregation of actionable information altogether. We examined the effectiveness of transformer-based LSTM-CRF architecture in Twitter-related sequence tagging tasks and simultaneously extracted actionable …

C³: Code Clone-Based Identification Of Duplicated Components, Yanming Yang, Ying Zou, Xing Hu, David Lo, Chao Ni, John C. Grundy, Xin: Xia

Research Collection School Of Computing and Information Systems

Reinventing the wheel is a detrimental programming practice in software development that frequently results in the introduction of duplicated components. This practice not only leads to increased maintenance and labor costs but also poses a higher risk of propagating bugs throughout the system. Despite numerous issues introduced by duplicated components in software, the identification of component-level clones remains a significant challenge that existing studies struggle to effectively tackle. Specifically, existing methods face two primary limitations that are challenging to overcome: 1) Measuring the similarity between different components presents a challenge due to the significant size differences among them; 2) Identifying …

Prompting And Evaluating Large Language Models For Proactive Dialogues: Clarification, Target-Guided, And Non-Collaboration, Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation. However, they still possess limitations, such as failing to ask clarifying questions to ambiguous queries or refuse users’ unreasonable requests, both of which are considered as key aspects of a conversational agent’s proactivity. This raises the question of whether LLM-based conversational systems are equipped to handle proactive dialogue problems. In this work, we conduct a comprehensive analysis of LLM-based conversational systems, specifically focusing on three key aspects of proactive dialogues: clarification, target-guided, and non-collaborative dialogues. To trigger the proactivity of …

A Black-Box Attack On Code Models Via Representation Nearest Neighbor Search, Jie Zhang, Wei Ma, Qiang Hu, Shangqing Liu, Xiaofei Xie, Yves Le Traon, Yang Liu

Research Collection School Of Computing and Information Systems

Existing methods for generating adversarial code examples face several challenges: limted availability of substitute variables, high verification costs for these substitutes, and the creation of adversarial samples with noticeable perturbations. To address these concerns, our proposed approach, RNNS, uses a search seed based on historical attacks to find potential adversarial substitutes. Rather than directly using the discrete substitutes, they are mapped to a continuous vector space using a pre-trained variable name encoder. Based on the vector representation, RNNS predicts and selects better substitutes for attacks. We evaluated the performance of RNNS across six coding tasks encompassing three programming languages: Java, …

A Big Data Approach To Augmenting The Huff Model With Road Network And Mobility Data For Store Footfall Prediction, Ming Hui Tan, Kar Way Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Conventional methodologies for new retail store catchment area and footfall estimation rely on ground surveys which are costly and time-consuming. This study augments existing research in footfall estimation through the innovative integration of mobility data and road network to create population-weighted centroids and delineate residential neighbourhoods via a community detection algorithm. Our findings are then used to enhance Huff Model which is commonly used in site selection and footfall estimation. Our approach demonstrated the vast potential residing within big data where we harness the power of mobility data and road network information, offering a cost-effective and scalable alternative. It obviates …

Class Participation: Using Technology To Enhance Efficiency And Fairness, Benjamin Gan, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

Class participation can be considered as contribution to discussion, attendance, presentations, unsolicited responses, questions, comments, etc. What counts may vary across individual teachers. The more students participate, the less memorization they do, and the more they engage in higher levels of thinking, including interpretation, analysis, and synthesis. However, only a handful of students in many classrooms participate regularly, a phenomenon dubbed as "consolidation of responsibility". This study provides a literature review of inclass participation, as well as pedagogies and technologies that enhance participation. Pedagogies such as active learning, group learning, project-based learning and flipped classroom. Technologies to automate attendance taking, …

Prompting And Evaluating Large Language Models For Proactive Dialogues: Clarification, Target-Guided, And Non-Collaboration, Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation. However, they still possess limitations, such as failing to ask clarifying questions to ambiguous queries or refuse users' unreasonable requests, both of which are considered as key aspects of a conversational agent's proactivity. This raises the question of whether LLM-based conversational systems are equipped to handle proactive dialogue problems. In this work, we conduct a comprehensive analysis of LLM-based conversational systems, specifically focusing on three key aspects of proactive dialogues: clarification, target-guided, and non-collaborative dialogues. To trigger the proactivity of …

Ethical Considerations For Artificial Intelligence In Educational Assessments, Lim Ming Soon Tristan, Gottipati Swapna, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

In the vital context of education, the application of artificial intelligence (AI) to assessments necessitates a nuanced examination of the boundaries between ethically permissible and impermissible practices. In this chapter, the authors applied a systematic literature mapping methodology to scour extant research, so as to holistically structure the landscape into explicit topical research clusters. Through topic modelling and network analyses, research mapped key ethical principles to different assessment phases in a triadic ontological framework. The chapter looks to provide researchers and practitioners the insights into the ethical challenges that exist across an end-to-end assessment pipeline.

Godel, Escherian Staircase And Possibility Of Quantum Wormhole With Liquid Crystalline Phase Of Iced-Water - Part I: Theoretical Underpinning, Victor Christianto, T. Daniel Chandra, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

As a senior physicist colleague and our friend, Robert N. Boyd, wrote in a journal (JCFA, Vol. 1,. 2, 2022), Our universe is but one page in a large book [4]. For example, things and Beings can travel between Universes, intentionally or unintentionally. In this short remark, we revisit and offer short remark to Neil’s ideas and trying to connect them with geometrization of musical chords as presented by D. Tymoczko and others, then to Escher staircase and then to Jacob’s ladder which seems to point to possibility to interpret Jacob’s vision as described in the ancient book of Genesis …

Use Of Ai To Recreate And Repatriate Lost, Destroyed Or Stolen Paintings: The 1785 Parisian Salon Case Study, Charles E. O'Brien, James Hutson, Trent Olsen, Jay Ratican

Faculty Scholarship

This study investigates the efficacy of artificial intelligence (AI) in the field of artwork restoration, focusing on lost, stolen, or destroyed artworks. Employing a dual approach that combines traditional manual restoration techniques with advanced generative AI tools, the research centers on a case study of the 1785 Parisian Salon. It specifically examines the reconstitution of Antoine François Callet's painting, Achilles Dragging the Body of Hector, unveiled alongside Jacques-Louis David's Oath of the Horatii. The study utilizes Easy Diffusion and Stable Diffusion 2.1 technologies for inpainting and colorization processes. These AI tools are employed in concert with manual restoration practices to …

Essence As Algorithm: Public Perceptions Of Ai-Powered Avatars Of Real People, James Hutson, Jay Ratican, Colleen Biri

Faculty Scholarship

This paper investigates the intersection of generative AI, Large Language Models (LLM), and robotics. Exemplified by systems like ChatGPT and technological marvels such as Ameca the Robot, the combination of technologies will allow humans to transcend the limitations of death. Through digital necromancy, a practice encompassing the technological resurrection of deceased individuals, the ability to not only passively see recordings of loved ones but to interact with them is made possible, leading to ethical and psychological considerations. Therefore, examining these trends extends into the motives underlying engagement with both incorporeal and corporeal reproductions of individuals, with reasons ranging from memory …

In Situ Water Sensing Systems: Research On Advancements In Environmental Monitoring, Abigail Seibel

Honors Theses

In this work, two sensing systems were researched in order to improve in situ environmental monitoring. The first is a pH and Total Alkalinity sensor used to determine these characteristics of sea water. I explored the facets of this sensor over a 7-week internship with Dr. Ellen Briggs in her lab in summer of 2023. The second is a more holistic sensing system that reads temperature, turbidity, and pressure used for studying environmental characteristics of Alaskan bever ponds. Both systems were developed in close collaboration with scientists who are collecting data to better understand the impacts of climate change. Better …

Kinematic Vorticity And Porphyroclast Rotation In Mylonites Of The Norumbega Fault System: Implications For Paleoviscometry, Hendrik Lenferink

Honors College

Crystallographic and shape preferred orientation (SPO) fabrics that develop in mylonitic shear zones can preserve the mean kinematic vorticity number (Wm) of bulk flow. Microstructural methods exploiting dynamically recrystallized quartz and porphyroclast SPO fabrics typically yield conflicting values of Wm. The Sandhill Corner Mylonite Zone of the Norumbega Fault System, Maine, USA, serves as a case study for investigating this discrepancy; Wm estimates range from 0.90 to 1.00 employing the former method (Method 1) and from 0.3 to 0.6 employing the latter method (Method 2). Using a numerical model, I show how a low-viscosity layer (LVL) surrounding clasts affects their …

Phosphorus Dynamics In Calcareous Soils Amended With Organic Matter, Logan Banner

All Graduate Reports and Creative Projects, Fall 2023 to Present

Phosphorus (P) is considered immobile in calcareous soils. Organic matter is known to enhance P mobility in these soils. Few studies have considered what role iron oxides might play in P sorption in calcareous soils, especially in the presence of soluble organic matter. This study investigated P sorption dynamics in sand-based, simulated soil systems in the absence or presence of 5 mM carbon (C) as humic acid (HA). Treatments included combinations of dicalcium phosphate dihydrate (DCPD), calcite, and ferrihydrite. Solutions containing 10 mg P L^-1 in a background of 0.01 M CaCl₂were equilibrated with each solid treatment …

Solar Flare Prediction From Extremely Imbalanced Multivariate Time Series Data Using Minimally Random Convolutional Kernel Transform, Kartik Saini

All Graduate Theses and Dissertations, Fall 2023 to Present

Solar flares are characterized by sudden bursts of electromagnetic radiation from the Sun's surface, and caused by the changes in magnetic field states in solar active regions. Earth and its surrounding space environment can suffer from various negative impacts caused by solar flares ranging from electronic communication disruption to radiation exposure-based health risks to the astronauts. In this paper, we address the solar flare prediction problem from magnetic field parameter-based multivariate time series (MVTS) data using multiple state-of-the-art machine learning classifiers that include MINImally RandOm Convolutional KErnel Transform (MINIROCKET), Support Vector Machine (SVM), Canonical Interval Forest (CIF), Multiple Representations SEQuence …

Generative Adversarial Game With Tailored Quantum Feature Maps For Enhanced Classification, Anais Sandra Nguemto Guiawa

Doctoral Dissertations

In the burgeoning field of quantum machine learning, the fusion of quantum computing and machine learning methodologies has sparked immense interest, particularly with the emergence of noisy intermediate-scale quantum (NISQ) devices. These devices hold the promise of achieving quantum advantage, but they grapple with limitations like constrained qubit counts, limited connectivity, operational noise, and a restricted set of operations. These challenges necessitate a strategic and deliberate approach to crafting effective quantum machine learning algorithms.

This dissertation revolves around an exploration of these challenges, presenting innovative strategies that tailor quantum algorithms and processes to seamlessly integrate with commercial quantum platforms. A …

The Influence Of Ion-Ion Correlations On Conductivity In Concentrated Ionic Systems, Md Dipu Ahmed

Masters Theses

This study delves into the fascinating realm of concentrated ionic systems, such as ionic liquids, superionic materials, organic ionic plastic crystals, and polyelectrolytes, which hold immense potential for energy storage applications. The focus is on understanding the intricate role of ionic correlations in shaping their ionic conductivity behavior. These correlations can either boost or impede conductivity, yet their underlying mechanisms remain elusive. Through extensive investigation of various materials, including ionic liquids with differing anionic masses, pure organic ionic plastic crystals, and doped systems, this research employs advanced techniques like dielectric spectroscopy and innovative momentum conservation models to quantify these correlations. …

Investigation Of The Chemical And Electronic Structure Of A 2h Phase Mos2 Single Crystal, Mary Blankenship

UNLV Theses, Dissertations, Professional Papers, and Capstones

Molybdenum disulfide has a wide range of applications in energy conversion devices, like thin-film solar cells, batteries, bio sensors, and more. Although the properties of MoS2 and other transition metal dichalcogenides (TMDC) have been widely studied, disagreements and discrepancies regarding its electronic structure remain.

In this thesis, a highly-oriented synthetic 2H phase MoS₂ single crystal is investigated using a toolchest of spectroscopic techniques to uncover its chemical and electronic properties. Lab-based x-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS), inverse photoemission spectroscopy (IPES), and low energy electron diffraction (LEED) were performed at UNLV and combined with resonant inelastic soft …

Travel Time Theory For Traffic Conservation Laws With Applications, Sergio Contreras

UNLV Theses, Dissertations, Professional Papers, and Capstones

Travel time is an important concept in various intelligent transportation system (ITS) applications. The concept is used in a wide array of applications, such as system planning, system performance, and optimization. Reducing the time required to travel between different points on a network is an important goal. Benefits include reducing time wasted in traveling, and keeping travelers satisfied. Thus, studying and reducing travel time in ITS is beneficial in different applications.

The classic density-based Lighthill Whitman Richards (LWR) equation for modeling traffic flow is the starting point in this dissertation. A more recent travel time dynamics function built on top …

Examining Covid-19 Vaccine Hesitancy Among The Nevada African American Population Using The Social-Ecological Model, Katelyn Faulk

UNLV Theses, Dissertations, Professional Papers, and Capstones

In Nevada, COVID-19 vaccines have been widely available to the general population since March 2021; however, even with the wide availability of these vaccines only 40% of the African American population in Nevada has been fully vaccinated against COVID-19 as of May 2023. This is problematic as it has been shown that the African American population is disproportionately affected by COVID-19 with higher rates of cases, hospitalizations, and deaths when compared to other races or ethnicities. Through the literature, it has also been well documented that African Americans may experience hesitancy toward these vaccinations for a multitude of reasons including …

Scalable Algorithm Design And Performance Analysis For Graph Motifs Discovery, Md Abdul Motaleb Faysal

UNLV Theses, Dissertations, Professional Papers, and Capstones

Discovering motifs or structural patterns, such as communities, is a significant graph application utilized for classifying groups in social and business networks, identifying similar proteins, detecting anomalous behavior in the cybersecurity domain, and finding critical entities in rumor propagation or infectious disease spreading. Existing state-of-the-art techniques for community discovery face challenges related to scalability, performance limitations, and methodological inaccuracies. The objective of this doctoral dissertation is to introduce novel parallel algorithms and propose high-performance computing architecture designs to address the performance constraints of current community detection approaches when processing large-scale social and biological data. This research focuses on two main …

Interaction Of Technetium (Iv) With Dibutyl Phosphate In N-Dodecane, Jonathan George

UNLV Theses, Dissertations, Professional Papers, and Capstones

During the reprocessing of nuclear fuel, the degradation of tributylphosphate (TBP) occurs as a result of radiolytic and thermal processes. These processes lead to the formation of minor amounts of dibutyl phosphate (HDBP). However, the presence of DBP poses a challenge in the partitioning of uranium (U), plutonium (Pu), and technetium (Tc) due to its chelating effects. The chelation of these elements by HDBP can interfere with their intended separation and purification, thereby impacting the efficiency and effectiveness of the reprocessing process. In this study, X-ray Absorption Fine Structure (XAFS) spectroscopy is employed to investigate the speciation of Tc following …

The Room Temperature Electrolysis Of F-Elements In Aqueous And Ionic Liquid Media: Synthesis, Dissolution, And Reduction, Phillip George Hammer

UNLV Theses, Dissertations, Professional Papers, and Capstones

Procuring F-element metals is no simple task and often requires the use of caustic and hazardous materials at high temperatures. These materials are invaluable for a variety of scientific missions ranging from the elucidation of fundamental properties, as fast spectrum nuclear fuel forms, to pit production modernizing our nuclear stockpiles. Metallic actinide materials are essential to strategic and critical materials recovery, the nuclear energy sector, and weapons production. Room temperature electrolysis is envisioned as a process to recover laboratory scale (milligram to gram) quantities of actinide metals. This process closes the uranium chemical loop allowing the reclamation of materials for …

Investigating Van Der Waals Josephson Junctions With 2h-Nbse2 And 1t’-Wte2, Kristine Lorraine Haley

UNLV Theses, Dissertations, Professional Papers, and Capstones

Josephson junctions have garnered significant attention due to their unique electronic properties and applications in quantum devices. In this thesis, we investigate the fabrication processes and characterization of two-dimensional (2D) Josephson junctions consisting of layered van der Waals materials: niobium diselenide (2H-NbSe₂) and few layered tungsten ditelluride (1T’-WTe₂). The reduction of dimensionality can bring forth unique characteristics in certain materials that are not seen in their bulk counterparts, making them prime candidates for physical exploration. 2H-NbSe₂ is an s-wave superconductor at temperatures near and below 7 K. 1T’-WTe₂ is a semimetal in bulk but …

Examining The Spatial Periodicity Of Force Chains And Strain Localization In Polycrystal Models, Richard D. Panduro-Allanson

UNLV Theses, Dissertations, Professional Papers, and Capstones

Shear strain localization is typical in deforming rocks and is vital for developing faults and tectonic boundaries. There are various proposed drivers of shear localization (temperature, fluid, phase transformation, and microstructure); we will explore the effects of elastic heterogeneity (a microstructural influence) on shear localization in polycrystal models. Elastic heterogeneity can lead to varied stress states in material and drive shear localization. Previous simulations of elastically heterogeneous polycrystal models have shown that the stress distribution can be described as forming an anastomosing pattern of high-stress streams parallel to the compression direction. This anastomosing patterning resembles force chains; linear, high-stress features …

Implementation Of Adas And Autonomy On Unlv Campus, Zillur Rahman

UNLV Theses, Dissertations, Professional Papers, and Capstones

The integration of Advanced Driving Assistance Systems (ADAS) and autonomous driving functionalities into contemporary vehicles has notably surged, driven by the remarkable progress in artificial intelligence (AI). These AI systems, capable of learning from real-world data, now exhibit the capability to perceive their surroundings via a suite of sensors, create optimal routes from source to destination, and execute vehicle control akin to a human driver.

Within the context of this thesis, we undertake a comprehensive exploration of three distinct yet interrelated ADAS and Autonomy projects. Our central objective is the implementation of autonomous driving(AD) technology at UNLV campus, culminating in …

New Observations On The Age And Origin Of The Geologist Seamounts, South Hawaiian Seamount Province, Brandon Chester Scott

UNLV Theses, Dissertations, Professional Papers, and Capstones

Investigation into seamounts that stem from intraplate volcanism—that is volcanism occurring far from plate boundaries—presents an opportunity to deconvolve processes associated with mantle compositional heterogeneities and melting dynamics. Upwelling and decompression of thermochemically anomalous mantle plumes is the primary mechanism for significant intraplate volcanism; however, many seamounts dotted across the Pacific Plate do not correlate spatially, temporally, or geochemically with mantle plume volcanism. One region of enigmatic volcanism in the ocean basins that is not clearly attributable to plume-derived magmatism are the Geologist Seamounts and the wider South Hawaiian Seamount Province (∼19°N, 157°W). Here we present merged multibeam (<100 m) and satellite altimetry bathymetric maps of the Geologist Seamounts region, new ^{40 …}

Actinide Behavior In Soft Ligand Environments And Higher Oxidation States Of Neptunium In Aqueous Media With Solid-State Synthesis Of Np(Vii) Compounds, Kelly Floyd Seeley

UNLV Theses, Dissertations, Professional Papers, and Capstones

The fundamental properties of Uranium and Neptunium were investigated with Powder X-Ray Diffraction (PXRD) to study the behavior or 5f electrons with chalcogen, alkali metals, and alkaline earth metals. Two novel compounds were generated: NaCuUS₃ and NaCuNpS₃. There are several crystal structures that form in the family of AMM’Q (A = s-block, M = d-block, M’ = d-block or f-block, and Q = chalcogen), with oxidation states of A¹⁺, M¹⁺, M’⁴⁺, and Q^2- ions from the family of type I compounds. Work was continued to …