Personalized Learning Path Problem Variations: Computational Complexity and AI Approaches

Excerpt: E-learning courses often suffer from high dropout rates and low student satisfaction. One way to address this issue is to use Personalized Learning Paths (PLPs), which are sequences of learning materials that meet the individual needs of students. However, creating PLPs is difficult and often involves combining knowledge graphs, student profiles, and learning materials. Researchers typically assume that the problem of creating PLPs belong to the NP-Hard class of computational problems. However, previous research in this field has neither defined the different variations of the PLP problem nor formally established their computational complexity. Without clear definitions of the PLP variations, researchers risk making invalid comparisons and conclusions when they use different metaheuristics for different PLP problems

Impact of Dilute Amounts of Fission Products on the Mechanical Behavior of Ni

ission products may interact with structural materials in various nuclear energy applications and cause their mechanical performance to deteriorate. Therefore, it is important to study the effects of different fission products on the mechanical properties of structural materials. In this work, nickel was chosen as a model structural material system and dilute amounts of uranium and fission product impurities X = (Tc, Te, Sb, Ce, Eu, and U) up to 4 at % were used. Density functional theory (DFT) calculations were utilized to assess the effects of these substitutional impurities on the elastic behavior of the metal. Additionally, DFT was used to investigate some aspects of plastic response by computing the generalized stacking fault energies on the {111} ⟨112⟩ slip system for all alloying elements and at varying distances away from the stacking fault plane. None of the dopants satisfied the Pugh or Pettifor criteria for embrittlement, and alloying with Tc led to a slight increase in the elasticity of nickel. The phenomenon of Suzuki segregation was observed for all alloying elements, and there was consequently a significant reduction in the intrinsic stacking fault energy. Finally, and based on the analysis of the stacking fault energies, dopants generally led to softening the nickel (except for Tc and Ce), and all of the dopants were correlated with a loss of ductility (except Eu). These findings may be useful to consider in the design of next-generation reactors and nuclear waste management system

Effects of a Modified Heat Treatment on the Quasi-static and Dynamic Behavior of Additively Manufactured Lattice Structures

The flexibility of additive manufacturing techniques that produce parts from powders layer-by-layer directly from a digital model enabled the fabrication of complex lightweight lattice structures with precisely engineered mechanical properties. Herein, an investigation of the quasi-static and dynamic behavior of additively manufactured (AM) triply periodic minimal surface (TPMS) lattice structures before and after a novel post-process heat treatment step is conducted. The specimens were fabricated out of Inconel 718, a nickel–chromium-based superalloy, using a selective laser melting technique with three different topologies, namely, gyroid, primitive, and I-WP. The quasi-static tests were conducted at a strain rate of 0.002 s-1 and dynamic experiments were conducted using a split Hopkinson pressure bar at three different strain rates, 600 s-1, 800 s-1, and 1000 s-1. It was shown that while the strain rate does not significantly affect the mechanical responses of the lattice structures, the heat treatment step dramatically changes their behavior. Results demonstrated that after the heat treatment, the yield strength of the I-WP specimens increased by 65.2% under a quasi-static load. Also, flow stress after yielding in the dynamic tests was shown to increase around 9.6% for I-WP specimens and up to 12.8% for gyroid specimens. The specific energy absorption values were 10.5, 19.1, and 10.7 for I-WP, gyroid, and primitive, respectively, before the heat treatment, and changed to 19.6, 19.8, and 15.4 after the heat treatment. The results confirm that by precisely designing the architecture of a lattice structure and implementing a modified heat treatment process, it is possible to optimize the weight, strength, and energy absorption capability of this type of metamaterial

Esoclinic subspaces, covers of the complete graph, and complex conference matrices

In 1992, Godsil and Hensel published a ground-breaking study of distance-regular antipodal covers of the complete graph that, among other things, introduced an important connection with equi-isoclinic subspaces. This connection seems to have been overlooked, as many of its immediate consequences have never been detailed in the literature. To correct this situation, we first describe how Godsil and Hensel\u27s machine uses representation theory to construct equi-isoclinic tight fusion frames. Applying this machine to Mathon\u27s construction produces ℝq+1 equi-isoclinic planes in Rq+1 for any even prime power q \u3e 2. Despite being an application of the 30-year-old Godsil–Hensel result, infinitely many of these parameters have never been enunciated in the literature. Following ideas from Et-Taoui, we then investigate a fruitful interplay with complex symmetric conference matrices

Air Force Institute of Technology Research Report 2021

This report summarizes the research activities of the Air Force Institute of Technology\u27s Graduate School of Engineering and Management, as well as AFIT\u27s research centers. It describes research interests and faculty expertise; list student theses/dissertations; identifies research sponsors and contributions; and outlines the procedure for contacting entities within the Institution

Assessing Compounding Risks of Airfield Flooding

At Tyndall AFB, an installation that is highly vulnerable to extreme weather, researchers piloted a unique approach that leverages high-resolution hydrologic-hydraulic models to illuminate resilience concerns affecting drainage systems during compounding climate events

GNSS Software Defined Radio: History, Current Developments, and Standardization Efforts

Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on field programmable gate array and application-specific integrated circuit platforms. Data collection systems (i.e., front-ends) have always been of paramount importance for GNSS SDRs and are thus partly covered in this work. This report represents the knowledge of the authors but is not meant as a complete description of SDR history

Study Protocol: Identifying Transcriptional Regulatory Alterations of Chronic Effects of Blast and Disturbed Sleep in United States Veterans

Injury related to blast exposure dramatically rose during post-911 era military conflicts in Iraq and Afghanistan. Mild traumatic brain injury (mTBI) is among the most common injuries following blast, an exposure that may not result in a definitive physiologic marker (e.g., loss of consciousness). Recent research suggests that exposure to low level blasts and, more specifically repetitive blast exposure (RBE), which may be subconcussive in nature, may also impact long term physiologic and psychological outcomes, though findings have been mixed. For military personnel, blast-related injuries often occur in chaotic settings (e.g., combat), which create challenges in the immediate assessment of related-injuries, as well as acute and post-acute sequelae. As such, alternate means of identifying blast-related injuries are needed. Results from previous work suggest that epigenetic markers, such as DNA methylation, may provide a potential stable biomarker of cumulative blast exposure that can persist over time. However, more research regarding blast exposure and associations with short- and long-term sequelae is needed. Here we present the protocol for an observational study that will be completed in two phases: Phase 1 will address blast exposure among Active Duty Personnel and Phase 2 will focus on long term sequelae and biological signatures among Veterans who served in the recent conflicts and were exposed to repeated blast events as part of their military occupation. Phase 2 will be the focus of this paper. We hypothesize that Veterans will exhibit similar differentially methylated regions (DMRs) associated with changes in sleep and other psychological and physical metrics, as observed with Active Duty Personnel. Additional analyses will be conducted to compare DMRs between Phase 1 and 2 cohorts, as well as self-reported psychological and physical symptoms. This comparison between Service Members and Veterans will allow for exploration regarding the natural history of blast exposure in a quasi-longitudinal manner. Findings from this study are expected to provide additional evidence for repetitive blast-related physiologic changes associated with long-term neurobehavioral symptoms. It is expected that findings will provide foundational data for the development of effective interventions following RBE that could lead to improved long-term physical and psychological health

Mo-Re-W Alloys for High temperature Applications: Phase stability, elasticity, and thermal property insights via multi-cell Monte Carlo and machine learning

The increasing demand for materials capable of withstanding high temperatures and harsh environments necessitates the discovery of advanced alloys. This study introduces a computational routine to predict solid-state phase stability and calculates elastic constants to determine high temperature viability. With it, machine learning models were trained on 1,014 Mo-Re-W structures to enable a large compilation of elastic and thermal properties over the complete Mo-Re-W compositional domain with extreme resolution. A series of heat maps spanning the full compositional domain were generated to visually present the impact of alloy constituents on the alloy properties. Our findings identified a balanced (Mo,W) + Re blend as a promising composition for high temperature applications, attributed to a strong and stable (Mo,W) matrix with high Re content and the formation of strengthening (W,Re) precipitates that enhanced mechanical performance at 1600°C. Several Mo-Re-W compositions were manufactured to experimentally validate the computational predictions. This approach provides an efficient and system-agnostic pathway for designing and optimizing alloys for high-temperature applications

Equi-isoclinic subspaces from symmetry

We describe a flexible technique that constructs tight fusion frames with prescribed transitive symmetry. Applying this technique with representations of the symmetric and alternating groups, we obtain several new infinite families of equi-isoclinic tight fusion frames, each with the remarkable property that its automorphism group is either Sn or An. These ensembles are optimal packings for Grassmannian space equipped with spectral distance, and as such, they find applications in block compressed sensing