Computer Sciences Commons^™

The Impact Of Student Engagement Activities On Future Climate Change Adaptation: The Case Of Student Simulation Models, Bassel Mostafa Elkalaf

Future Journal of Social Science

This paper explores the critical role of student engagement in addressing the growing challenges of climate change, with a focus on the Model United Nations (MUN) as a case study. As climate-related security threats increase globally, educational platforms that prepare youth for effective leadership in climate politics are more essential than ever. MUN, a widely practiced student activity simulating global policy-making, provides a valuable opportunity for students to deepen their understanding of the interconnectedness between climate change, peace, and security. By participating in MUN simulations, students engage in debates, develop innovative solutions, and practice diplomatic skills, all while exploring the …

Universal Shape Replication Via Self-Assembly With Signal-Passing Tiles, Andrew Alseth, Daniel Hader, Matthew J. Patitz

Computer Science and Computer Engineering Faculty Publications and Presentations

In this paper, we investigate shape-assembling power of a tile-based model of self-assembly called the Signal-Passing Tile Assembly Model (STAM). In this model, the glues that bind tiles together can be turned on and off by the binding actions of other glues via “signals”. Specifically, the problem we investigate is “shape replication” wherein, given a set of input assemblies of arbitrary shape, a system must construct an arbitrary number of assemblies with the same shapes and, with the exception of size-bounded junk assemblies that result from the process, no others. We provide the first fully universal shape replication result, namely …

Multi-Criteria Decision-Making Approach Based On Correlation Coefficient For Multi-Polar Interval-Valued Neutrosophic Soft Set, Hamza Naveed, Saalam Ali

Neutrosophic Systems with Applications

The correlation coefficient between two factors is crucial in statistical computation, indicating the extent and evolution of the appropriate link. The precision of applicability evaluations frequently relies on the thoroughness and caliber of data obtained from a certain dataset. Statistical research sometimes entails data marked by intrinsic trade-offs and uncertainty. This study seeks to present m-polar interval-valued neutrosophic soft sets (mPIVNSSs) through the integration of m-polar fuzzy sets with interval-valued neutrosophic soft sets. The suggested mPIVNSS structure is a significantly generalized version of m-polar neutrosophic soft sets and serves as a substantial extension of interval-valued neutrosophic soft sets. In this …

Neutrosophic Cox Proportional Hazards Model For Robust Variable Selection In Survival Analysis, Ibrahim Yasser, Aya A. Abd El-Khalek, A. A. Salama, Doaa A. Abdo

Neutrosophic Systems with Applications

This paper introduces a novel approach for variable selection in survival analysis by integrating neutrosophic logic into the Cox Proportional Hazards (Cox PH) model to address the limitations of recent studies related to high dimensionality. Neutrosophic logic, is a mathematical framework that allows for uncertainty, indeterminacy, and inconsistency, and particularly well suited for handling the complexity and often-ambiguous nature of biological data. By incorporating neutrosophic sets into the Cox PH model, we aim to enhance model robustness, improve variable selection, and address the curse of dimensionality. We compare the performance of the neutrosophic-enhanced Cox PH model with traditional variable selection …

On Neutrosophic Pδs-Irresolute Functions In Neutrosophic Topological Spaces, Bishnupada Debnath, Anjan Mukherjee

Neutrosophic Systems with Applications

In general topology the notion of pds-irresolute and aδs-irresolute functions were introduced by Beceren and Noiri. In the present paper, these concepts of pδs-irresolute (briefly, Npδs-irresolute) and aδs-irresolute (briefly, Naδs-irresolute) functions are explored for the first time in neutrosophic topological spaces (NTS) as generalized version. We proved that every Naδs-irresolute function is Npδs-irresolute function but not conversely. Some characterizations, counter examples, and fundamental features are also presented. By neutrosophic pre-open, neutrosophic δ-open, and neutrosophic δ-semi-open sets, some new fundamental properties of such functions are provided. Furthermore, under Npδs-irresolute functions, the behavior of neutrosophic semi-connected, neutrosophic pre-connected, neutrosophic pre-T2, neutrosophic δ-semi-T2, …

Analysis Of Bck/Bci-Algebras Based On Bipolar Complex Intuitionistic Fuzzy Soft Ideals, Zeeshan Ali

Neutrosophic Systems with Applications

In this article, we design an informative and reliable technique of bipolar complex intuitionistic fuzzy soft sets with numerous operational laws by merging the model of soft sets, complex fuzzy sets, and bipolar intuitionistic fuzzy sets to handle imprecise data. In addition, an ideal in a BCK-algebra is derived based on bipolar complex intuitionistic fuzzy soft set theory are proposed which can capture the information of hesitancy, vagueness, and non-membership information within the circumstance of BCK-algebra. Moreover, we design union, intersection, AND, and OR based on bipolar complex intuitionistic fuzzy soft ideal and simplify it with the help of numerous …

Comparative Analysis Of Multi-Criteria Techniques In Neutrosophic Environment And Their Applications To Economic Condition Assessment, Asmaa Elsayed, Mai Mohamed

Neutrosophic Systems with Applications

In economic decision-making, the challenge of evaluating multiple, often conflicting criteria necessitates advanced Multi-Criteria Decision-Making (MCDM) techniques. Traditional methods can struggle with the inherent uncertainty, ambiguity, and imprecision of real-world data. This paper addresses these challenges by investigating the effectiveness of various MCDM techniques within neutrosophic environments, with a particular focus on the Criteria-wise Alternatives Ranking and Correlation Analysis for Composite Scoring (CARCACS) method. Neutrosophic sets, which incorporate truth, falsity, and indeterminacy, provide a robust framework for addressing the vagueness and inconsistencies found in economic indicators such as GDP growth, employment levels, inflation rates, trade balances, investment activity, and government …

Learning To Represent Temporal Dynamics And Generative Factors For Intelligent Visual Navigation, Sahand Khoshdel

All Theses

Visual navigation systems are crucial in various applications, including autonomous driving, unmanned aerial systems (UAS), and industrial automation. For these systems to operate efficiently in dynamic environments, they must not only interpret complex surroundings but also anticipate changes over time. Temporal prediction—forecasting environmental changes like moving obstacles or shifting lighting conditions—enables navigation systems to act proactively, enhancing both safety and performance. This dissertation investigates representation learning methods both as a backbone feature extractor for RL agents as well as a proxy for systems oriented for Explainable AI (XAI). Two main projects are presented as case studies to achieve the aforementioned …

Patterns Of Interactions In Human-Machine Teams, Kazuhiko Momose

Theses and Dissertations

Increasingly capable machines, including Artificial Intelligence (AI) agents are playing a more important role in a wide range of applications, including human daily activities and safety-critical systems. They can benefit even more when humans and such machines agents work together as a team by leveraging each other's strengths and complementing each other to enhance overall performance. To design high-performing teams, it is critical to analyze the team dynamics and understand how humans and machines interact with each other. Collaboration, Coordination, and Cooperation (3Cs) are terms typically used to describe the behavior of teams. However, these terms tend to be used …

Basic Safety Message Generation Through A Video-Based Analytics For Potential Safety Application, Abyad Enan

All Theses

With the advancement of modern artificial intelligence techniques, computer vision can play a vital role in enhancing roadway safety by reducing the risk of imminent collisions. To do so, a vision-based safety application is required, where a roadside camera can monitor the roadway traffic and predict potential risks of crashes in real-time. If any risky situation or behavior is observed that may lead to a crash, then a safety application can send warnings to the vehicles at risk. For vision-based safety applications on a roadway section, it is important to accurately monitor each vehicle’s location, speed, acceleration, heading direction, etc. …

Clusteredlog: Optimizing Log Structures For Efficient Data Recovery And Integrity Management In Database Systems, Mariha Siddika Ahmad, Brajendra Panda

Electrical Engineering and Computer Science Faculty Publications and Presentations

In modern database systems, efficient log management is crucial for ensuring data integrity and facilitating swift recovery from potential data corruption or system failures. Traditional log structures, which store operations sequentially as they occur, often lead to significant delays in accessing and recovering specific data objects due to their scattered nature across the log. ClusteredLog addresses the limitations of traditional logging methods by implementing a novel logical organization of log entries. Instead of simply storing operations sequentially, it groups related operations for each data item into clusters. As a result, ClusteredLog enables faster identification and recovery of damaged data items …

Dynamic Key-Based Privacy-Preserving Authentication Scheme For Internet Of Drones, Zain Chaudhary

Honors Theses

The Internet of Drones (IoD) proliferation has catalyzed transformative changes across various industries, from agriculture to urban management. However, expanding drone networks also presents significant security challenges concerning secure communication and authentication. This paper introduces a robust privacy-preserving key-based authentication scheme tailored explicitly for the IoD, utilizing a matrix key generated by Hierarchical Message Authentication Codes (HMAC) and the SHA-256 algorithm to address these vulnerabilities. Our system enhances security by ensuring each drone in the network can authenticate securely and reliably with a central unit, preventing unauthorized access and securing communications against common threats like eavesdropping and impersonation attacks. Our …

Using Symbolic Execution To Analyze The Hardware Tcp Protocol, Nianhang Hu

School of Computing: Dissertations, Theses, and Student Research

As the demand for high performance and flexible networking capabilities increases, the shift from software to hardware implementations of stateful networking functions (such as TCP) is becoming increasingly important. This transition not only enhances processing efficiency in modern networking environments where data transmission rates are rising, but it also reduces the inherent CPU overhead found in software implementations, allowing hardware devices to handle network traffic more efficiently. However, validating the correctness of these hardware designs poses significant challenges due to the complex timing requirements and the vast input space associated with packet-level properties.

The verification of packet-level properties requires coverage …

Not All Samples Are Created Equal: Task-Aware Informative Sampling And Adaptive Inference For Efficient Edge Ai, Rebati Gaire

School of Computing: Dissertations, Theses, and Student Research

The rapid proliferation of Internet of Things (IoT) devices has resulted in an unprecedented influx of data generated at the edge by billions of sensors. Traditional approaches relying on cloud-based processing are increasingly inadequate due to constraints in bandwidth, latency, and privacy. Edge computing has emerged as a transformative paradigm, enabling real-time data processing and decision-making by decentralizing computation to the edge. While the integration of deep learning into edge environments—termed edge intelligence—promises autonomous and personalized operations, it is hindered by challenges such as limited computational resources, energy constraints, and data redundancies.

This thesis addresses these challenges by presenting three …

Prevalence Of Autism Spectrum Characteristics In Students Taking Undergraduate Computing Courses, Rachel Michaela Mettenbrink

School of Computing: Dissertations, Theses, and Student Research

The incidence rate of autism spectrum condition (ASC) has increased significantly in recent decades, as awareness of the condition and its impacts increases amongst clinicians, parents, and the general population. Medical literature has proposed that there may be a relationship between ASC and participation in the computing field. This study tests for the prevalence of autism spectrum condition traits measured by delivering the Autism Spectrum Quotient (AQ) to a population of undergraduate computer science students. We examine the relationships between AQ scores and students taking undergraduate computer science classes, sex, socioeconomic status, and parents in the computing industry. Additionally, we …

Neural Network Architecture Search Enabled Wide-Deep Learning (Nas-Wd) Integrated Hyperspectral Imaging Understanding For Woody Breast In Poultry Processing, Chaitanya Kumar Reddy Pallerla

Graduate Theses and Dissertations

The development and implementation of a Wide & Deep (WD) learning model tailored for classification and regression tasks utilizing spectral data provides a robust solution to evaluate woody breast (WB) conditions in poultry fillets. This process begins with thorough data preprocessing, which includes loading spectral and classification datasets, imputing missing values with medians, and splitting the data into training and testing sets to ensure rigorous model evaluation. The WD model architecture integrates wide linear models and deep neural networks to harness the strengths of both approaches. The wide component excels at memorizing sparse feature interactions, while the deep component captures …

Controller Software: Evolution, Identification, And Implementation, Balaji Balasubramaniam

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

In the annals of automation history and advancement, one can find control technology is at the core. Modern-day controllers rely heavily on software capability to provide stability and improve the system's performance. In particular, drone flight controllers use autopilot control software to accomplish autonomous navigation from take-off to landing. However, we know very little about how the controller code modifications and its impact, particularly at the software level. No general framework has been developed to identify the control code changes and observe the real values of software control loops at the kernel layer.

In this thesis, we lay the foundation …

Deep Learning Vision-Based Bridge Inspection With Resource-Constrained Unmanned Aircraft Systems, Ji Young Lee

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Bridge inspection is critical for ensuring structural integrity, extending the service life of infrastructure, and minimizing maintenance costs. As bridges age and endure increasing loads, regular inspections help detect early signs of wear, such as cracks or corrosion, that could impact safety and performance. However, traditional inspection methods are labor-intensive, requiring significant time, specialized equipment, and manual access to challenging areas, which can lead to costly disruptions. Additionally, reliance on human inspectors introduces subjectivity, with assessments varying by individual expertise. These factors highlight the inefficiencies and safety risks in current inspection practices, underscoring the need for more objective, efficient solutions. …

Reference Dependence In Queue Design And Pricing Strategies, Jian Liu, Yongpin Zhou, Jian Chen, Peng Li

Electrical and Computer Engineering Faculty Research & Creative Works

This research investigates the effect of reference dependence on waiting times in service systems which formerly used a first-in-first-out (FIFO) service but have introduced a priority line with a fee. Our model combines reference-dependent gain-loss utility with standard customer utility, and we posit that customers are pleased with shorter-than-expected waiting times, whereas longer-than-expected times lead to dissatisfaction and an increased likelihood of balking. The study explores two scenarios: a captive customer system (CCS) and a noncaptive customer system (NCCS), with a focus on optimal pricing and segmentation strategies for revenue and social welfare maximization. The results reveal that, in a …

Populations Digitally Excluded From Education: Issues, Factors, Contributions And Actions For Policy, Practice And Research In A Post-Pandemic Era, Don Passey, Jean Gabin Ntebutse, Manal Yazbak Abu Ahmad, Janet Cochrane, Simon Collin, Asmaa Ganayem, Elizabeth Langran, Sadaqat Mulla, Ma. Mercedes T. Rodrigo, Toshinori Saito, Miri Shonfeld, Saunand Somasi

Department of Information Systems & Computer Science Faculty Publications

This conceptual paper draws on a wide range of research and policy literature, providing a contemporary view of issues, factors and practices that affect education for digitally excluded populations. Concern for how education for digitally excluded populations can be supported is focal to this paper, with different sections offering key related perspectives. From an analysis of issues, factors and practices, actions for policy, practice and research are identified. Given a key finding that power issues can have major effects on plans, implementation processes and outcomes when addressing needs of education for digitally excluded populations, the paper concludes by offering frameworks …

On Neutrosophic Pδs-Irresolute Functions In Neutrosophic Topological Spaces, Bishnupada Debnath, Anjan Mukherjee

Neutrosophic Systems with Applications

In general topology the notion of pds-irresolute and aδs-irresolute functions were introduced by Beceren and Noiri. In the present paper, these concepts of pδs-irresolute (briefly, Npδs-irresolute) and aδs-irresolute (briefly, Naδs-irresolute) functions are explored for the first time in neutrosophic topological spaces (NTS) as generalized version. We proved that every Naδs-irresolute function is Npδs-irresolute function but not conversely. Some characterizations, counter examples, and fundamental features are also presented. By neutrosophic pre-open, neutrosophic δ-open, and neutrosophic δ-semi-open sets, some new fundamental properties of such functions are provided. Furthermore, under Npδs-irresolute functions, the behavior of neutrosophic semi-connected, neutrosophic pre-connected, neutrosophic pre-T2, neutrosophic δ-semi-T2, …

Comparative Analysis Of Multi-Criteria Techniques In Neutrosophic Environment And Their Applications To Economic Condition Assessment, Asmaa Elsayed, Mai Mohamed

Neutrosophic Systems with Applications

In economic decision-making, the challenge of evaluating multiple, often conflicting criteria necessitates advanced Multi-Criteria Decision-Making (MCDM) techniques. Traditional methods can struggle with the inherent uncertainty, ambiguity, and imprecision of real-world data. This paper addresses these challenges by investigating the effectiveness of various MCDM techniques within neutrosophic environments, with a particular focus on the Criteria-wise Alternatives Ranking and Correlation Analysis for Composite Scoring (CARCACS) method. Neutrosophic sets, which incorporate truth, falsity, and indeterminacy, provide a robust framework for addressing the vagueness and inconsistencies found in economic indicators such as GDP growth, employment levels, inflation rates, trade balances, investment activity, and government …

Quantum Visual Feature Encoding Revisited, Xuan-Bac Nguyen, Hoang-Quan Nguyen, Hugh Churchill, Samee U. Khan, Khoa Luu

Computer Science and Computer Engineering Faculty Publications and Presentations

Although quantum machine learning has been introduced for a while, its applications in computer vision are still limited. This paper, therefore, revisits the quantum visual encoding strategies, the initial step in quantum machine learning. Investigating the root cause, we uncover that the existing quantum encoding design fails to ensure information preservation of the visual features after the encoding process, thus complicating the learning process of the quantum machine learning models. In particular, the problem, termed the “Quantum Information Gap” (QIG), leads to an information gap between classical and corresponding quantum features. We provide theoretical proof and practical examples with visualization …

Computational Representation, Analysis And Verification Of Requirements In Engineering Design And Systems Engineering, Chandan Kumar Sahu

All Dissertations

Systems are developed to satisfy a set of requirements derived from stakeholders’ needs, defining the problem space for which the system is created as a feasible solution. The system design process begins with eliciting these requirements and concludes with validating whether the created system meets them. Requirements engineering (RE) encompasses elicitation, representation, analysis, documentation, verification, and validation. However, challenges in RE, such as imprecision in natural language (NL), proprietary restrictions, and a lack of standardized quality metrics, hinder the creation of well-formed and comprehensive requirements. These challenges complicate formalization and analysis of requirements.

This dissertation addresses these challenges by proposing …

Protocol Transformations Across Osi Network Stack Layers For Attack, Evasion, And Defense, Nathan Tusing

All Dissertations

Network endpoints frequently contend with errors and deviations within protocols. Many factors account for these deviations including noise, tampering, and algorithm implementations. Intermediate nodes are expected to modify instantiated protocols and not guarantee correctness. This ability to modify traffic enables all sides of network security to alter security and performance properties of protocols, and we define this intermediary modification of an instantiated protocol as a transformation. Protocol transformations traverse layers of the OSI reference model and changes a protocol's time series byte sequence. Within this thesis, we show that this framework applies to multiple domains and protocols. Common examples of …

Neutrosophic Cox Proportional Hazards Model For Robust Variable Selection In Survival Analysis, Ibrahim Yasser, Aya A. Abd El-Khalek, A. A. Salama, Doaa A. Abdo

Neutrosophic Systems with Applications

This paper introduces a novel approach for variable selection in survival analysis by integrating neutrosophic logic into the Cox Proportional Hazards (Cox PH) model to address the limitations of recent studies related to high dimensionality. Neutrosophic logic, is a mathematical framework that allows for uncertainty, indeterminacy, and inconsistency, and particularly well suited for handling the complexity and often-ambiguous nature of biological data. By incorporating neutrosophic sets into the Cox PH model, we aim to enhance model robustness, improve variable selection, and address the curse of dimensionality. We compare the performance of the neutrosophic-enhanced Cox PH model with traditional variable selection …

Multi-Criteria Decision-Making Approach Based On Correlation Coefficient For Multi-Polar Interval-Valued Neutrosophic Soft Set, Hamza Naveed, Saalam Ali

Neutrosophic Systems with Applications

The correlation coefficient between two factors is crucial in statistical computation, indicating the extent and evolution of the appropriate link. The precision of applicability evaluations frequently relies on the thoroughness and caliber of data obtained from a certain dataset. Statistical research sometimes entails data marked by intrinsic trade-offs and uncertainty. This study seeks to present m-polar interval-valued neutrosophic soft sets (mPIVNSSs) through the integration of m-polar fuzzy sets with interval-valued neutrosophic soft sets. The suggested mPIVNSS structure is a significantly generalized version of m-polar neutrosophic soft sets and serves as a substantial extension of interval-valued neutrosophic soft sets. In this …

Analysis Of Bck/Bci-Algebras Based On Bipolar Complex Intuitionistic Fuzzy Soft Ideals, Zeeshan Ali

Neutrosophic Systems with Applications

In this article, we design an informative and reliable technique of bipolar complex intuitionistic fuzzy soft sets with numerous operational laws by merging the model of soft sets, complex fuzzy sets, and bipolar intuitionistic fuzzy sets to handle imprecise data. In addition, an ideal in a BCK-algebra is derived based on bipolar complex intuitionistic fuzzy soft set theory are proposed which can capture the information of hesitancy, vagueness, and non-membership information within the circumstance of BCK-algebra. Moreover, we design union, intersection, AND, and OR based on bipolar complex intuitionistic fuzzy soft ideal and simplify it with the help of numerous …

A Data-Driven Approach For Automated Multi-Site Competitive Facility Location, Ming Hui Tan, Kar Way Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper addresses the challenge of optimal retail expansion in competitive urban environments through a novel approach to the Competitive Facility Location (CFL) problem. Traditional methods for solving CFL problems often struggle with large-scale scenarios, relying on manual pre-selection of candidate sites and imposing limitations on the number of new locations. Our approach leverages Adaptive Large Neighborhood Search (ALNS) enhanced with data enrichment techniques, including community detection on road networks and population weighting based on mobility data. We developed two ALNS variants: Community Geometric Centroid (CGC-ALNS) and Population Weighted Centroid (PWC-ALNS). These methods automate site selection, eliminating manual pre-selection while …

Mechanically Cost-Effective Approach For Bipedal Walking In Robots Using Instantaneous Collision Angle, Smit R. Patel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Humans, as bipedal locomotors, are effective at reducing the mechanical cost of transport (CoTmech) by adopting movement strategies and gaits that minimize energy expenditure for a given distance. By using different gaits at different speeds, leveraging their long spring-like tendons and muscle elasticity which store and release energy during movement, humans reduce the mechanical effort required for locomotion. Current locomotion solutions offered in bipedal robots, based on legacy walking and running gait models, are not great at energy efficiency unless walking at very low speeds. Additionally, the control system of robots, designed to ensure stability and adaptability, requires substantial resources, …