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Exploring Inventions in Self-Directed Language Learning with Generative AI: Implementations and Perspectives of YouTube Content Creators
Get PDFThis study explores the integration of generative AI, specifically ChatGPT, in selfdirected language learning (SDLL) as perceived by YouTube content creators. Through thematic analysis of in-depth interviews with 14 prominent online language educators with related YouTube videos on ChatGPT, the present study investigates: (1) their perceptions of GenAI as a tool for SDLL, (2) strategies that they recommend to effectively utilize ChatGPT for enhancing SDLL, and (3) the guidelines they suggest for fostering SDLL with AI. The findings show that YouTube-based language educators acknowledged ChatGPT as a vital tool for SDLL as it offers availability, versatility, and transformative potential. Besides linguistic benefits, ChatGPT enhances SDLL experiences by generating contextually relevant responses and fostering meaningful conversations and learner growth. The study highlights the importance of addressing ethical, pedagogical, and sociocultural factors when incorporating AI in SDL and educators’ critical role in facilitating learners’ navigation through the evolving landscape of SDL in the age of generative AI. The study contributes to refining online language learning models and comprehending the impact of generative AI on SDL
Stormwater Management in Flat Floodplains
Get PDFCommunities across the Midwest have experienced chronic stormwater drainage and increased flooding of roadways and structures. While adequate storm drainage seems to be lacking in many rural communities, steps can be taken to address some of the nuisance flooding that plagues many regions. Walnut Township commissioned a stormwater study that included the development of a 2D model to understand and mitigate flooding in their area
Broadband Equity, Access, and Deployment (BEAD) Program
Get PDFThe federal government will allocate 100 million or more for unserved areas. This is a transformative opportunity for Indiana municipalities, but those without a clear plan risk missing out. Join us as we cover essential steps for securing broadband funds, applications, permits, and safe installations. Don’t miss the chance to benefit from this infrastructure investment
County Bridge Preservation: Locally Funded vs. Federally Funded
Get PDFThis presentation will discuss the previous federal aid call for bridge preventative maintenance projects, the INDOT Asset Management Plan format vs. CCMG, how the federal aid call was cancelled, and how Harrison County and Boone County moved projects forward with 100% local funds. We will also explore how far counties have come on asset management with pavements, and the continuing need adopt preventative maintenance on bridges. We will conclude with an overview of how these projects can be delivered locally vs. with federal funds
Burnout: How to Spot It and Take Action
Get PDFEvery project’s goal is to meet or exceed scope, schedule, and budget. However, despite excellent project management, employee burnout can hinder this objective. Burnout causes employees to lose focus, make mistakes, and take longer to finish tasks. Burnout is also terrible for your short and long-term well-being. This presentation will identify early indicators of burnout and offer a recovery plan that can help employees recover from burnout and prevent it from occurring again
Small Structure Inspection & Reporting
Get PDFSmall structure inspections (those under 20 ft) are often overlooked but are crucial when maintaining highway infrastructure. While not mandatory, INDOT and FHWA recommend routine inspections every 4 to 6 years. Identifying these structures beneath our roadways is vital for timely repairs or replacements and can prevent costly emergencies. A robust inspection program sup- ported by tools like USI’s IVY software, ensures efficient data management and enables agencies to plan and act proactively based on inspection results
SAFERoad Solutions: Explaining Road Designs to the Public
No full textSAFERoad Solutions is a guide to designs that improve safety, mobility, and efficiency across roadways. This online toolkit was created for the Kentucky Transportation Cabinet to explain both innovative and standard road designs to the public and to serve as a resource for engineers and other transportation officials. This presentation will highlight the SAFERoad Solutions guide, explain how to effectively communicate transportation topics to the public, and provide methods to creating content and specific topics
A predictive model for fin array boiling heat transfer performance under two-phase immersion cooling
No full textHeat sinks with extended surface area can enhance the pool boiling performance for two-phase immersion cooling of electronic devices. However, even for a simple heat sink geometry with an array of longitudinal fins, predicting performance during boiling is challenging. Individual fins can be modeled as extended surfaces with a superheat-dependent heat transfer coefficient based on flat surface boiling performance, but this approach fails in the limit of closely spaced fin arrays because of fin-vapor interactions. Recent studies have identified the fluid capillary length Lb as the key length scale at which such vapor confinement effects must be considered to accurately predict the performance of finned heat sinks in pool boiling. In this study, we propose a predictive model for the pool boiling heat transfer performance of a fin array heat sink, valid across all dimensions above and below the capillary length. The model follows a fin analysis with a constant base superheat and a heat transfer coefficient that is dependent on local fin surface superheat. This fin-specific function hfin(ΔT) is determined from an empirically calibrated function hflat(ΔT) obtained from a flat surface boiling test with the same surface characteristics. For fin spacing above the capillary length (S \u3e Lb), hflat(ΔT) can be directly applied as hfin(ΔT). Whereas for fin spacing below the capillary length (S \u3c Lb), vapor confinement effects enhance boiling heat transfer at lower heat fluxes and deteriorate performance at higher heat fluxes; these confinement effects are incorporated as mechanistic modifications to the function hflat(ΔT). Boiling tests are conducted to validate the prediction accuracy of the model. In particular, the vapor confinement effects on fin array heat sinks with tight fin spacing are well-captured by the model. Furthermore, the effects of fin height and spacing on the boiling performance of fin array heat sinks are explored by applying the experimentally validated model. The predictive model provides a tool for designing and optimizing the heat sinks for two-phase immersion cooling applications and provides insight into the dimensional scaling effects on the boiling performance of fin arrays
Leveraging LiDAR Intensity to Evaluate Roadway Pavement Marking Retroreflectivity
Get PDFClearly visible lane markings are important for all road users, particularly autonomous vehicles. In general, nighttime retroreflectivity is one of the most challenging marking visibility characteristics for agencies to monitor and maintain, particularly in cold weather climates when agency snowplows remove retroreflective material during winter operations. Traditional surface-applied paint and glass beads typically only last one season in climates with routine snowplow activity. Recently, transportation agencies in cold weather climates have begun deploying improved recessed, durable pavement markings that can last several years and have very high retroreflective properties. These recessed durable markings are typically either epoxy, thermoplastic or preformed tape and are typically installed during new construction or significant pavement resurfacing projects. As a result, several dozen installations may occur in a state in any calendar year. This presents a challenge for states that need to program annual re-painting of traditional waterborne paint lines, but not paint over the much more costly durable markings.
This study reports on the utilization of mobile mapping LiDAR systems to classify and evaluate pavement markings along a 73-mile section of westbound I-74 in Indiana. LiDAR intensity data can classify pavement markings into 3 groupings: high-performing durable tape, non-tape, and needing maintenance. Color images collected during the LiDAR intensity data collection were used to validate the LiDAR classification. These techniques can be employed by agencies to develop accurate pavement marking inventories that ensure only painted lines (or segments with missing tape) are repainted during annual maintenance
