VTechWorks
VTechWorks provides global access to Virginia Tech scholarship, including journal articles, books, theses, dissertations, conference papers, slide presentations, technical reports, working papers, administrative documents, videos, images, and more by faculty, students, and staff. Faculty can deposit items to VTechWorks from Elements, including journal articles covered by the University open access policy. Email vtechworks@vt.edu for help.
Open Access Policy
Virginia Tech's open access policy enables researchers to deposit the accepted version of scholarly articles with no embargo.
Theses and Dissertations
Virginia Tech was first in the world to require ETDs in 1997, and continues to add scans of older theses and dissertations.
Open Textbooks
More than 50 freely available and openly licensed textbooks are among our most downloaded items.
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Recent Submissions
Evaluation of ACC and AVG Combination as a New Tool for Managing Pre-Harvest Fruit Drop and Improving Red Color in ‘Honeycrisp’ Apples
Tipu, Mohammad; Jahed, Khalil R.; Sherif, Sherif M. (Virginia Cooperative Extension, 2025-06-27)
Pre-harvest fruit drop (PFD) poses a major challenge in apple production, often leading to significant yield losses. This phenomenon is closely associated with the fruit’s ripening process, during which the phytohormone ethylene plays a critical role by promoting cell wall breakdown, ultimately leading to fruit detachment (Tipu and Sherif, 2024). At the same time, achieving adequate red peel coloration— primarily due to anthocyanin accumulation— is essential for marketability, especially in bi-colored cultivars like ‘Honeycrisp’. Ethylene also plays a central role in regulating this color development. This dual role creates a fundamental dilemma: while ethylene is essential for desirable coloration, it simultaneously increases the risk of fruit drop (Tipu et al., 2025).
To combat PFD, growers often apply aminoethoxyvinylglycine (AVG), commercially known as “ReTain” (Valent BioSciences), which effectively reduces drop by inhibiting ethylene biosynthesis (Liu et al., 2022). However, the major drawback of using AVG is that by reducing ethylene, it also hinders the development of red color (Miah and Farcuh, 2024), resulting in fruit that may stay on the tree but fail to meet market color standards, creating a difficult trade-off between preventing yield loss and achieving desired quality.
Addressing this challenge requires alternative strategies that can balance drop control with optimal coloration. This publication highlights the potential benefits of combining AVG with 1-aminocyclopropane-1-carboxylic acid (ACC), the immediate precursor of ethylene. Emerging evidence suggests that ACC may have signaling functions independent of its conversion to ethylene (Polko and Kieber, 2019). The core concept— that an AVG-ACC combination can help reduce pre-harvest fruit drop without compromising color— was detailed with physiological, biochemical, and molecular evidence in a peer-reviewed article by Tipu et al. (2025). This current report presents a grower-focused summary, distilling the key messages from that work and offering a practical solution to the ongoing challenge of balancing fruit retention and coloration.
Evaluating Benefits of Improved Oceanic Air Traffic and Airfield Management Through Computer Simulation
Zolfaghari, Armin (Virginia Tech, 2026-10-21)
This dissertation develops and enhances computer simulation capabilities for evaluating operational and infrastructure improvements across two important components of the air transportation system: oceanic airspace and airport runways. Although these components involve different operational environments, both require realistic modeling of aircraft behavior to evaluate strategies for increasing capacity and operational efficiency while reducing fuel consumption, delays, and environmental impacts.
This research enhances two fast-time simulation tools, the Global Oceanic (GO) model and the Runway Exit Design Interactive Model (REDIM), using operational data and improved aircraft performance modeling to replicate real-world aircraft operations better and support air transportation planning and decision-making.
The GO model was enhanced by implementing conflict detection and resolution procedures based on the Federal Aviation Administration's (FAA's) Advanced Technologies and Oceanic Procedures (ATOP), developing an origin-destination-based traffic forecasting methodology, and improving aircraft Takeoff Weight (TOW) estimation by incorporating effects of oceanic wind conditions and reserve fuel requirements on TOW. The enhanced model was applied to North Atlantic (NAT) and Pacific operations to evaluate the benefits of advanced surveillance and navigation technologies that reduce aircraft separation standards in the mentioned oceanic regions. For the NAT, reduced separation standards resulted in up to approximately 66% fewer aircraft conflict-resolution maneuvers, up to approximately $272 million in estimated annual fuel-cost savings, and up to approximately 1.1 billion kg of annual emissions reductions. For Pacific operations, conflict-resolution maneuvers were reduced by up to 68%, with estimated annual fuel savings of approximately 64.7 million kg. Validation against real-world fuel-consumption data demonstrated that the GO model replicated observed fuel-consumption trends with an average accuracy of approximately 96.7% for the most common aircraft types operating in NAT airspace.
REDIM was enhanced using more than 38 million Airport Surface Detection Equipment, Model X (ASDE-X) landing profiles to realistically represent aircraft landing behavior and estimate Runway Occupancy Time (ROT) by incorporating differences between reverse-turn and flow-through maneuvers on high-speed exits, and the effects of runway-to-parallel-taxiway distance on pilot behavior on exits. Statistical and empirical analysis showed that there are significant differences between reverse-turn and flow-through operations. Also, runway-to-parallel-taxiway distance strongly affects pilot behavior on exits. Validation of the enhanced REDIM against ASDE-X observations resulted in Mean Absolute Errors of approximately 0.86 seconds for flow-through operations and 0.95 seconds for reverse-turn operations. In addition, an Aircraft Characteristics Database containing validated characteristics for 387 aircraft types was developed to support REDIM and other airport planning applications.
Overall, this dissertation demonstrates the value of computer simulation for evaluating improvements across both oceanic airspace and airport runways. The enhanced GO model provides a more realistic framework for evaluating advanced oceanic technologies and reduced separation standards, while the enhanced REDIM provides reliable evaluation of runway-exit configurations and estimation of ROT. Together, these tools support aviation stakeholders in evaluating strategies to accommodate future air traffic demand more efficiently.
Intelligent eXtended Reality (iXR): A Systematic Review of Intelligent Context-Aware Adaptations in XR
Alimoradi, Saeid; Gabbard, Joseph L.; Bowman, Douglas A. (2026)
Extended Reality (XR) interfaces situate digital content in the user's surroundings, and their effectiveness depends on how well the interface fits the user's situation. Context-aware XR systems address this fit through a detect-reason-adapt pipeline, in which contextual data is detected, inferred by a reasoning mechanism, and returned to the interface as a real-time adaptation. This study systematically reviews the extent to which existing XR systems are intelligent across this pipeline. Following the PRISMA framework, records were retrieved from Scopus, IEEE, and ACM, and 158 studies were analyzed along three dimensions: the source, type, and contextual category of the detected environmental, task, and/or user data; the reasoning mechanism and the output it produces; and the adaptation strategy and the interface elements it changes. The results show that the three layers are developed to unequal depths. Detection concentrates on user context, task context is rarely detected directly, and reliance on a single sensing channel is common. Context reasoning divides almost evenly between learning-based and non-learning mechanisms and learning-based models are mature only at percept extraction while situational interpretation remains hand-engineered. Adaptation is the shallowest layer, as most systems map an inferred condition to a fixed, predetermined change confined to the visibility and placement of content. Based on these findings, the review defines Intelligent XR (iXR) as a system with an identifiable learning or inference mechanism in both the reasoning and adaptation layers, supported by sufficient sensing breadth, within an interactive latency threshold.
Pseudoinverse Training for Neuromorphic Reservoir Computing Using Square-Root-Free Cholesky Decomposition
Ling, Jiaqiang (Virginia Tech, 2026-10-06)
Adaptive reservoir readouts require a compact training engine as well as an efficient inference circuit. This thesis develops a fixed-point, square-root-free readout trainer for a windowed echo state network used in MIMO-OFDM symbol detection. The trainer streams regularized sufficient statistics into a banked, packed memory, factors the 48-by-48 normal matrix in place with a reciprocal-based LDL-transpose decomposition, and reuses the factors for all four real outputs. A word-length analysis of the datapath shows that the statistics multipliers can be narrowed from 48 by 48 bits to 14 by 14 and 14 by 17 bits without changing any result bit, reducing DSP usage from 162 to 36 slices on the Zynq ZCU104. For the factorization, a standard eigenvalue argument shows that ridge regularization bounds every reciprocal operand by the inverse of the regularization constant. This bound sets the required operand range and explains why a smaller 32-bit factor/solve option, which uses 26 DSP slices, passes tests with strong regularization but rejects every recorded packet it was tested on at the regularization used for detection. The selected design, implemented in the detection configuration, uses 36 DSP slices, 31,488 LUTs, and 27 block-RAM tiles, meets a fully constrained 50 MHz out-of-context timing requirement with an estimated 69 mW of dynamic power, and completes a 540-sample training batch in 147,146 cycles, or 2.943 ms. In RTL simulation of 19,230 recorded frames from 30 recordings in five scenarios, it trains every frame and reproduces all 3,692,160 reference weights exactly. With these weights, the ESN detector reaches a bit error rate of 4.05 percent over all frames, against 5.78 percent for LS/ZF and 4.90 percent for baseline MMSE detection, and is the better of the three in four of the five scenarios; pilot-tracked conventional detectors remain more accurate. A triplet-STDP circuit study is also summarized, and the adaptation of the trainer to GlobalFoundries 40LP is identified as ongoing work.
Europeanization and De-Europeanization in the Eastern Partnership Countries
Brantly, Aaron F.; Vasilyan, Syuzanna; Seferian, Nareg; Nuriyev, Elkhan; Brantly, Nataliya D.; Tsuladze, Lia; Pântea, Serghei; Rabinovych, Maryna; Leshchyshyn, Anastasia; Hlomb, Marta; Popova, Maria (West Point Press, 2026-10-05)
Europeanization and De-Europeanization in the Eastern Partnership Countries examines how states on the EU eastern borders navigate the promises and limits of integration. Challenging linear accounts of Europeanization, it introduces de-Europeanization to show how alignment with EU norms can stall, shift, or reverse. Through comparative analyses of Armenia, Azerbaijan, Belarus, Georgia, Moldova, and Ukraine, the volume highlights how domestic politics, identity, security pressures, and economic interests shape divergent trajectories. Against Russia’s war in Ukraine and renewed enlargement debates, it assesses EU initiatives including European Neighborhood Policy and Eastern Partnership. The book shows European influence is actively negotiated rather than simply adopted.