Digital Commons Network^™

The Environment And Population Differences In Anjan Grass (Cenchrus Ciliaris) In Western India, S C. Pandeya

IGC Proceedings (1977-2023)

Cenchrus ciliaris (anjan or buffel grass) is a gregarious fodder species with high nutritive value. The species is an inhabitant of drier sandy areas throughout Africa, Canary Island, Madagascar and eastwards to India, where it mostly occurs in western parts of the country, constituting the States of Gujarat, Rajasthan, Hayana and the adjoining portions of Punjab, U ttar Pradesh and Madhya Pradesh ( called here in as Western India). In Western India, Cen­chrus ciliaris (Cc) variously dominates the nat­urally occurring grazing lands exhibiting great morphological variations with respect to habit. and spike characters. The ecoclimate of Western India is arid …

Comparative Analysis Of Task Scheduling In Multi-Tier Fog-Cloud Computing: From Classical Approaches To Greedy Multi-Objective Optimization, Zafril Rizal M. Azmi, Najmul Haque, Saydul Akbar Murad

Faculty Publications

Fog computing extends cloud services to the network edge, enabling low-latency processing for time-sensitive applications. However, scheduling complexity significantly increases due to heterogeneous resources, dynamic workloads, and strict Quality-of-Service (QoS) constraints. Although numerous scheduling techniques have been proposed, existing studies often assess only a narrow subset of algorithms or rely on offline metaheuristics unsuitable for real-time environments. This paper presents a comprehensive comparative evaluation of twelve scheduling algorithms, including five classical, one heuristic, and six metaheuristic-inspired approaches, within a realistic 20-node multi-tier fog-cloud topology. Across 1,365 experiments spanning seven utilization levels, we analyze each algorithm’s deadline adherence, load distribution, and …

Air: Improving Agent Safety Through Incident Response, Zibo Xiao, Jun Sun, Junjie Chen

Research Collection School Of Computing and Information Systems

Large Language Model (LLM) agents are increasingly deployed in practice across a wide range of autonomous applications. Yet current safety mechanisms for LLM agents focus almost exclusively on preventing failures in advance, providing limited capabilities for responding to, containing, or recovering from incidents after they inevitably arise. In this work, we introduce AIR, the first incident response framework for LLM agent systems. AIR defines a domain-specific language for managing the incident response lifecycle autonomously in LLM agent systems, and integrates it into the agent's execution loop to (1) detect incidents via semantic checks grounded in the current environment state and …

Prediction Of Satellite Temperature During An Orbit Of A Cubesat, Michael Reynolds

Honors Theses

This thesis develops a thermal-simulation strategy for predicting CubeSat component temperatures, applied to Jag-Sat-1, a CubeSat developed at the University of South Alabama and deployed from the International Space Station in 2022. The orbit was reconstructed from two-line element (TLE) data using simplified general perturbations (SGP4) propagation, and spacecraft attitude was recovered from onboard gyroscope measurements. Sunlight, penumbra, and umbra intervals were computed geometrically, and the external radiative environment — direct solar, Earth infrared, and albedo heat fluxes — was modeled using orientation-dependent view factors. These time-varying fluxes drove a transient finite-element thermal simulation of the full satellite geometry in …

On The Side And Angle Mixtures Expressed By Triangles: Phase Diagrams Based On Intensive State Properties, Daniel Graham

Chemistry: Faculty Publications and Other Works

This is a lecture packet focused on the side and angle mixtures of structures at the center of the planar geometry universe. The intensive states of triangles are charted with the help of phase diagrams—long-standing tools in chemical thermodynamics and materials science. The intended audience consists of students and teachers—college and high school—seeking fresh perspectives, projects, and discussion topics surrounding age-old systems.

Elemental Analysis Of Upper Devonian To Lower Mississippian Organic-Rich Mudstone Cores From Kentucky By Portable X-Ray Fluorescence (Pxrf), Alex M. Washburn

KGS Research Data Set

This dataset contains high-density portable X-ray fluorescence (pXRF) elemental analyses of 1,867 m (6,125 ft) of Upper Devonian to Lower Mississippian organic-rich mudstone cores from Kentucky. Analyses were collected from cores across the Illinois Basin, Cincinnati Arch, and Appalachian Basin to support regional evaluation of elemental variability, chemostratigraphy, and redox-sensitive trace-metal enrichment in Devonian–Mississippian mudstone successions. All measurements were conducted using a Bruker Tracer 5 pXRF analyzer with the factory “Mudrock Air” calibration, using analytical settings optimized for both low-atomic-number elements and transition metals/redox-sensitive trace elements. Reference materials SARM-41 and SGR-1 were analyzed throughout the analytical sequence to monitor instrument …

Analysis Of Clinical Health Worker Notes With Explainable Artificial Intelligence For A Better Perspective In Preventing Readmission, Christopher Scott Klimp

Theses and Dissertations from DePaul University

Emergency Department (ED) readmissions remain a major challenge for healthcare systems, affecting both patient care quality and financial costs. Most prediction models depend largely on structured data from clinical tools that assign points to a small set of predefined factors – such as comorbidities, previous hospital visits, and behaviors such as smoking and drinking – and then sum those points to produce an overall risk score. These point-based tools leave out important information from Social Determinants of Health and a wealth of information from Community Health Workers (Community health workers (CHWs), trusted members of a community who help connect people …

Rendering Data Unlearnable By Exploiting Llm Alignment Mechanisms, Ruihan Zhang, Jun Sun

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly trained on massive, heterogeneous text corpora, raising serious concerns about the unauthorised use of proprietary or personal data during model training. In this work, we address the problem of data protection against unwanted model learning in a realistic blackbox setting. We propose Disclaimer Injection, a novel data-level defence that renders text unlearnable to LLMs. Rather than relying on model-side controls or explicit data removal, our approach exploits the models’ own alignment mechanisms: injecting carefully designed alignment-triggers to prevent effective learning. Through layer-wise analysis, we find that finetuning on such protected data induces persistent activation …

There Is No Free Benchmark: An Institutional View Of Legal Ai Benchmarking, Neel Guha, Andy K. Zhang, Christine Tsang, Christopher D. Manning, Julian Nyarko, Daniel E. Ho

Faculty Scholarship

Despite substantial excitement around the use of AI in law, little information exists on the performance and associated risks of the domain’s widely marketed tools. Recent work, for instance, has demonstrated the significant potential for “hallucinations” — wherein models make up facts, law, and precedent — leading Chief Justice Roberts to spotlight this risk in his annual report on the judiciary. We argue that there is a need for public AI benchmarking in law. First, relative to other AI application domains, the legal AI ecosystem lacks legibility — there is little information about the design and performance of many commercial …

Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models, Chunyan Liu, Yan Lei, Huan Xie, Jinping Wang, Yue Yu, David Lo

Research Collection School Of Computing and Information Systems

Learning-based dynamic fault localization techniques play a crucial role in the field of software engineering. These techniques dynamically execute test cases to meticulously extract useful knowledge from the execution information in the program, with the aim of identifying fault locations by leveraging machine learning, deep learning, and large language models. Currently, there is already a flourishing body of research that is intensely focused on learning-based dynamic fault localization. Research literature can be categorized into two main aspects for learning-based dynamic fault localization: data-based enhancements (i.e., the datasets) and model-based enhancements (i.e., the suspiciousness algorithms). Thus, we conduct an extensive literature …

Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

This paper introduces a Knowledge‑State Generative Agent framework for evaluating the quality of pre‑assessment questions. The framework employs large language model (LLM)–based agents prompted to adopt a teacher persona to simulate the responses of students with and without mastery of targeted knowledge components. A preliminary empirical study using archival data from 424 students enrolled in an Information Systems Management course indicates that the proposed approach yields interpretable metrics under Classical Test Theory. Results further show that agents instantiated with the relevant mastered knowledge components exhibit systematically higher performance than agents lacking such mastery. In addition, the study suggests that teacher-persona …

Operational Agency: A Permeable Legal Fiction For Tracing Culpability In Ai Systems, Anirban Mukherjee, Hannah H. Chang

Research Collection Lee Kong Chian School Of Business

Modern artificial intelligence (AI) systems act with a high degree of independence yet lack legal personhood—a paradox that fractures doctrines grounded in human-centric notions of mens rea and actus reus. This Article introduces Operational Agency (OA)—a permeable legal fiction structured as an ex post evidentiary framework—and Operational Agency Graph (OAG)—a tool for mapping causal interactions among human actors, organizations, and AI systems. OA evaluates an AI’s observable operational characteristics: its goal-directedness (as a proxy for intent), predictive processing (as a proxy for foresight), and safety architecture (as a proxy for standard of care). OAG operationalizes that analysis by embedding these …

Ethos: A Computational Framework For Material Culture Research, Chelsea L. Grafe

Department of Textiles, Merchandising and Fashion Design: Dissertations, Theses, and Student Research

Museum catalog records make large collections searchable, but they do not always preserve the reasoning behind the claims they contain. A record may present a quilt's identity as settled while leaving the reasoning behind that claim invisible, making it difficult for later researchers to check, question, or reuse. This project asks whether museum catalog data can be analyzed in a way that keeps each analytical claim connected to the evidence that supports it. To test this question, the project applies a material-first computational framework named Ethos. Ethos formalizes an object-centered inquiry sequence in which material dependencies establish where analysis begins …

Crustal Structure Of The Vøring Plateau And Vøring Spur From Joint Refraction And Reflection Travel-Time Tomography, Anika Nawar Mayeesha

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Crustal architecture of the Vøring Plateau and Vøring Spur in the mid-Norwegian continental margin remains debated because the geophysical data in the area do not uniquely constrain whether the crust is continental, oceanic, or transitional. This study reanalyzes wide-angle ocean-bottom seismometer data from Profile 11-03 across the Vøring passive continental margin using joint travel-time tomography of crustal refractions and Moho reflections. A total of 6,760 first-arrival picks and 542 PmP picks from sixteen instruments were inverted for P-wave velocity and reflector depth. Three starting models were inverted independently to test sensitivity to the initial crustal configuration. The first two used …

An Emergent Seafood Nationalism Takes Hold In The United States, Owen Temby

School of Earth, Environmental, & Marine Sciences Faculty Publications

This paper introduces the concept of ‘seafood nationalism’ to describe how, since 2024–2025, the United States increasingly uses tariffs, trade remedies, food safety enforcement and origin-based rules to favour American seafood over foreign products. Federal actions include Executive Order 14276, Restoring American Seafood Competitiveness, which directs agencies to address unfair trade practices, unsafe imports and to develop a coordinated seafood trade strategy. Additional measures include a tariff package imposing a 10% duty on nearly all seafood imports and 30% on seafood from China, as well as new anti-dumping and countervailing duty orders on warm-water shrimp. This paper presents Gulf …

Anomaly Management In Unmanned Aerial Vehicles: A Systematic Literature Review, Ivan Tan Wei Han, Christopher M. Poskitt, Lingxiao Jiang, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Unmanned Aerial Vehicles (UAVs) are increasingly deployed in safety-critical applications such as logistics, surveillance, disaster response, and urban air mobility. While their autonomy enables powerful capabilities, it also introduces vulnerabilities due to hardware faults, software defects, communication failures, and adversarial interference. This survey presents a comprehensive review of research studies closely related to UAV anomalies published between 2015 and 2025, covering 111 papers from academic and industrial sources. We introduce a unified five-pillar taxonomy—anomaly generation, prevention, detection, recovery, and analysis—that organizes existing work across the full anomaly management lifecycle. In contrast to prior surveys that focus primarily on detection algorithms, …

Operationalizing Ethics For Ai Agents: How Developers Encode Values Into Repository Context Files, Christoph Treude, Sebastian Baltes, Marc Cheong

Research Collection School Of Computing and Information Systems

As AI coding agents become embedded in software development workflows, developers are beginning to operationalize ethical principles by encoding behavioral rules into repository-level context files for AI agents, such as AGENTS.md files. Rather than examining the ethics of AI agents in the abstract, this vision paper investigates how ethics and values are already being translated for AI agents into actionable instructions that shape agent behavior. Through a preliminary investigation, we find that developers are already embedding guidance related to fairness, accessibility, sustainability, tone, and privacy. These artifacts function as a developer-authored governance layer, translating abstract principles into situated, natural-language directives …

On The Side And Angle Mixtures Expressed By Triangles: Phase Diagrams Based On Intensive State Properties, Daniel Graham

Chemistry: Faculty Publications and Other Works

This is a lecture packet focused on the side and angle mixtures of structures at the center of the planar geometry universe. The intensive states of triangles are charted with the help of phase diagrams—long-standing tools in chemical thermodynamics and materials science. The intended audience consists of students and teachers—college and high school—seeking fresh perspectives, projects, and discussion topics surrounding age-old systems.

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …

Recent Advances In Phosphatidylinositol Phosphate Kinases (Pipks) And Their Inhibitors, Mengxia Sun, Jian Hu, Xuefei Huang

BAU Journal - Science and Technology

Phosphatidylinositol phosphate kinases (PIPKs) are an important class of enzymes in humans, which produce lipid signaling molecules playing central roles in pathogenesis of diseases such as cancer, neurodegenerative diseases, and viral infection. Consequently, they are attracting increasing attention as drug targets for disease treatment. This review summarizes the functions of the PIPK family enzymes and highlights recent efforts on designing novel inhibitors against PIPKs. These advances are extensively discussed to stimulate interest in this field and promote further development of highly potent and selective inhibitors for innovative therapeutic applications.

Exploiting Uncertainty Of Computational Methodology In Optimizing User Interface In Human-Computer Interaction, Nada Mohamed, Alshaimaa A. Tantawy

Neutrosophic Systems with Applications

Human-computer interaction (HCI) evaluation and optimization of user interfaces (UIs) constitute a complex multi-criteria decision-making challenge, marked by conflicting evaluation dimensions, subjective expert judgments, and inherent uncertainty in user experience assessment. Traditional evaluation approaches, such as heuristic expert reviews and user satisfaction surveys, rely on sharp, binary classifications that fail to capture the gradual and overlapping nature of human cognitive and affective states. This limitation necessitates a more robust uncertainty-aware methodology that can model the true complexity of HCI evaluation. This paper proposes a hybrid mathematical model that integrates various Multi-Criteria Decision Making (MCDM) techniques of Entropy, and Simple Additive …

Natural Radioactivity And Radiological Hazards In Sediments From The Lindi Coast, Indian Ocean, Tanzania, Viator Mujuni, Innocent J. Lugendo

Tanzania Journal of Science

The Lindi coast of the Indian Ocean, located in southeastern Tanzania, supports rich biodiversity and has recently experienced rapid growth in socio-economic activities such as fishing, mining, and oil and gas exploration. These activities may enhance levels of natural radioactivity in coastal sediments, potentially increasing radiation exposure to local populations. Therefore, monitoring radioactivity levels and estimating associated radiation doses in this region is important. In this study, thirty-six sediment samples were collected from twelve locations along the Lindi coast and analysed for naturally occurring radionuclides using high-purity germanium (HPGe) gamma-ray spectrometry. The activity concentrations of ²²⁶Ra, ²³²Th, and …

A Mathematical Model For Managing Diphtheria Outbreaks In Nigeria Via Vaccination, Enhanced Surveillance, Effective Quarantine, And Social Distancing Measures, Hycienth Ortser Orapine, Nyiutya Cephas Ine, Dekera Jacob Washachi, Ali Audu Baidu, Lubem Matthew Kwaghkor

Mathematical Modelling and Numerical Simulation with Applications

Diphtheria is a highly infectious respiratory and skin disease that poses a significant threat to global public health. In Nigeria, children and adults with low immunity remain at high risk due to recurring annual outbreaks in the last decade, with a death rate of as high as 68.8\%. This paper presents a deterministic compartmental model to evaluate the effectiveness of interventions implemented by the Nigerian government. The model's mathematical and epidemiological validity is established through proofs of non-negativity and boundedness. The basic reproduction number ($R_0$) is derived, and stability analysis confirms that the diphtheria-free equilibrium is locally and globally asymptotically …

Principal Leadership As A Predictor Of Teacher Performance: Evidence From An Indonesian Elementary School, Irminapinem Pinem, Antonius Remigius Abi, Hamela Sari Sitompul

Jurnal Pendidikan Sains

Teacher performance is a critical determinant of educational quality and student achievement, making the identification of factors that influence teacher effectiveness an important area of educational research. Among these factors, principal leadership has been recognized as a key organizational variable that shapes teachers’ professional practices and instructional performance. This study aimed to examine the relationship between principal leadership and teacher performance at State Elementary School Raya Kahean, Simalungun Regency, Indonesia. The study employed a quantitative correlational research design involving 52 teachers selected through total sampling. Data were collected using two structured questionnaires measuring principal leadership and teacher performance. The principal …

Modern Architecture Of Muqarnas In Damascus: An Original Computational Methodology, Nahed Jawad Chakouf

All Works

The research aimed to revive muqarnas using digital computational tools, drawing on the techniques of Damascene craftsmen and ancient manuscripts. It involved designing contemporary muqarnas with double-curvature vaults and large spans, incorporating new unit designs and compositional techniques. In Section I, the researcher conducted pre-design studies on four muqarnas types, each associated with one of the four Damascene architectural styles. These studies examined the geometry and behavior of muqarnas types when used on traditional domed surfaces. Section II included a design study of the Dome of the Eagle of the Umayyad Mosque in Damascus, using modern software tools such as …

Li+/Na+ Hybrid Ion Conduction Mechanism In The Superionic Conductor Li3–XNaXZr2Si2Po12, Yi-Hong Wu, Xia Xie, Lei Zhu, Mu-Ran Yu, Guo-Tai Zhang, Jun-Chao Chen, Shu-Ying Sun, You-Wei Wang, Wei-Ping Tang

Journal of Electrochemistry

Hybrid ion conductors that transport multiple ionic conductive species provide a useful platform for understanding how mixed-ion transport governs ionic conductivity within a single phase. However, the controlled introduction of multiple mobile ions into solid-state electrolytes and a mechanistic understanding of their migration within the framework remain challenging. Herein, a skeleton-retained Li⁺↔Na⁺ cationic exchange was used to simultaneously induce Li⁺ and Na⁺ cations into the NASICON-type framework of Li_3–xNa_xZr₂Si₂PO₁₂ (0 < x < 3). We show that the interpenetration of NaO₆ and NaO₈ coordination polyhedra significantly influences the ionic conductivity of hybrid ion conductors. Computational …

Study On Structural Design And Load Transfer Performance Of 6-Hole Flat Anchor Plate, Liao Yuanyuan, Ling Lihua, Wu Qibin, Cheng Bin, Dai Dongming

Journal of China & Foreign Highway

For negative bending moment prestressed tendons in simply supported-to-structurally-continuous bridges, the flat anchorage method of flange plate is more reasonable, but its widespread application is limited due to the anchoring capacity restrictions of flat anchor plates. To improve the anchoring capacity of a single anchorage zone, reduce the number of prestressed ducts, save concrete, and improve construction efficiency, a novel 6-hole flat anchor plate was developed, designed, and manufactured in this paper. By combining finite element analysis and experimental methods, a finite element analysis model of the concrete load transfer specimen beneath the novel 6-hole flat anchor plate was established, …

Analysis Of Shear Bearing Mechanism And Influencing Factors Of Mcl-Shaped Composite Dowel Connector, Zeng Zhuo, Zhou Baicheng, Cheng Xianjie, Cao Zhengxing, Gao Rongxiong, Wang Zichao

Journal of China & Foreign Highway

To investigate the bearing mechanism of modified clothoid (MCL)-shaped composite dowel shear connectors and the influence laws of various factors on their shear bearing capacity, the stress states and failure modes of the steel dowel, concrete dowel, and transverse through-reinforcement that constitute the MCL-shaped shear connector were deeply analyzed in this paper based on an experimentally validated finite element model. Furthermore, the influence laws of transverse through-reinforcement, steel dowel thickness, and concrete strength on the shear bearing capacity of the MCL-shaped composite dowel were explored. The research results indicate that the bearing process of the MCL-shaped composite dowel exhibits elastic, …

Research On Improving Bearing Capacity Of Full-Scale Prestressed Concrete Small Box Girders, Huang Jianyun, Gao Linli, Liu Zufeng, Ma Jinku, Ma Ming, Wang Xiaoguang

Journal of China & Foreign Highway

To solve the problems of lacking comparative research on the improvement effects of different reinforcement methods when formulating reinforcement schemes for prestressed concrete small box girders and that existing bearing capacity improvement tests mostly focus on scale models with insufficient reliability of results, full-scale model tests and numerical simulation analysis of five 30 m span prestressed concrete small box girders with different joint reinforcement measures were conducted in this paper. Finite element models for two single reinforcement measures were established, and the improvement effects of different reinforcement methods on the bearing capacity of prestressed concrete small box girders were studied. …

Research On Dic Monitoring Of Dynamic Deflection And Damage Identification Method For Small And Medium-Span Bridges, Wang Yong, Li Derui, Tang Haotian, Yan Xingfei, Cheng Bin

Journal of China & Foreign Highway

A large number of built small and medium-span bridges in China are facing the problem of increasingly degrading structural performance. Therefore, it is of great significance to carry out lightweight intelligent monitoring and realize damage identification and early warning, so as to ensure the safe operation of these bridges. For typical small and medium-span simply supported beam bridges, a damage analysis method based on measured dynamic deflection data was established by combining the influence line theory and mechanical constitutive equations. Furthermore, based on the high-precision monitoring algorithm and instruments of digital image correlation (DIC), the real-time dynamic deflection data of …