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Role of Retro Branding on a Consumer\u27s Attitude Toward Products and Purchase Intentions
Full text linkThis paper proposes retro branding as a marketing strategy that can impact consumers’ attitudes towards retro-branded products and, ultimately, their purchase intentions. Evoked nostalgia, through retro branding, for hedonic and utilitarian products is explored to investigate the impact on attitudes towards the products for both product types and purchase intentions. Nostalgia proneness is examined as a moderator amongst the relationships between retro branding, attitude towards products (both utilitarian and hedonic), and purchase intentions. Additionally, age and gender are explored as possible boundary conditions that impact the purchase intentions. Results indicate that evoked nostalgia, through retro branding, enhances attitudes toward products, positively influencing purchase intentions regardless of product type
Polyglot File Detection for Forensics
Full text linkPolyglot files are problematic as payloads can be hidden inside them while simultaneously evading discovery by current forensic tools. Autopsy, one of the most used forensic tools in investigations, uses known signatures of file types (e.g., headers, trailers) to identify and recover files. Polyglot files are a unique case in which files are intentionally combined with other file types to make them appear benign while still containing malicious payloads. Polyglots are possible due to combinations being considered valid in both formats. Polyglot files inherently evade detection from signature-based forensic tools and malware scanners because the tools and malware scanners are designed to search for a single type of file without additional validation. The challenge of detecting malicious files is further exacerbated by polyglot files appearing as benign in the file system. File systems are mainly concerned with managing file storage by checking file structures, but not necessarily their content. This is also true in forensic investigations where the payload embedded within the polyglot file is obfuscated. To address this, an algorithm is being evaluated that will utilize a data carving-based approach to perform block level analysis of a raw disk image to detect polyglot files.https://jagworks.southalabama.edu/southalabama-shgrf-posters/1006/thumbnail.jp
Pseudomonas aeruginosa ExoY Enzymatic Activity Inhibits ExoS-Induced Caspase-3/7 Activation but not Cytotoxicity in PMVECs
Full text linkPseudomonas aeruginosa (P. aer.) is the most common cause of ventilator associated pneumonia (VAP) in ICU patients. Different combinations of exoenzymes (S, T, Y, and U) are found in P. aer. strains. ExoY is most often associated with VAP in ICU patients. ExoY infection of pulmonary microvascular endothelial cells (PMVECs) induces cell rounding but does not activate intracellular caspase-3/7 or cause cell death. ExoS and ExoT infection of epithelial cells leads to caspase-3/7 dependent cell death. Previous studies using epithelial cells show that ExoY alleviates the cytotoxic effects of ExoS and ExoT. Here, we sought to determine whether ExoY inhibits ExoS and ExoT induced caspase-3/7 activation and cell death in PMVECs.https://jagworks.southalabama.edu/honors_college_posters/1038/thumbnail.jp
Joan Browning Presentation Reception Photo 2
No full textReception at the McCall Archive Library for Ms. Joan Browning after her presentation at the University of South Alabama.https://jagworks.southalabama.edu/freedom-rider-browning_photos/1011/thumbnail.jp
Joan Browning Presentation Reception Photo 5
No full textReception at the McCall Archive Library for Ms. Joan Browning after her presentation at the University of South Alabama.https://jagworks.southalabama.edu/freedom-rider-browning_photos/1014/thumbnail.jp
Forecasting Vehicle Energy Consumption based on User Driving Patterns
No full textThis paper proposes the prediction of vehicle Driving Energy Consumption (DEC) of based on the user’s driving style. This research focused on the Mobile, AL area. The dataset contains time-series data from a vehicle for six months. All essential data, such as speed, latitude, longitude, and elevation, were collected through the OBD-II port of the vehicles. Before data collection, a survey was conducted between May 2024 and April 2025. 215 participants participated in the survey and shared their viewpoints regarding Electric Vehicles (EVs), Dynamic Pricing (DP) , and driving behaviors. The qualitative survey data showed that the adoption of EVs is not directly related to age, income, or educational level. In addition, a geo-spatial analysis of home and work addresses showed that most of the users leave home early in the morning and return home in the evening. After collecting qualitative and quantitative data from the vehicle, the data was used to calculate the driving energy consumption (DEC). The DEC time-series data was used to train and test machine learning (ML) models to predict the DEC. Then, a logistic regression model is employed to predict the status of the vehicle. Integrating logistic regression with DEC prediction, the home-to-home driving energy (H2HDEC) is calculated for the next day. Robustness analysis of the pretrained models was done with the vehicle’s 7th-month data. The results confirm that the proposed models can capture underlying patterns and provide comparable performance for DEC prediction. The focus on DEC makes the algorithm developed in this research more robust and capable of predicting the energy for any vehicle type because any engine losses are not considered in DEC. The effective energy is calculated considering the average losses for EVs in this research, but the motor losses of any vehicle can be substituted for use with this algorithm
Designing the Future of Open Through Innovation: Integrating AI to Support Z-Degrees and Institutional Transformation
Full text linkJosh leads and initiative at Hillsborough College that is among the first in the nation to integrate artificial intelligence with Open Educational Resources (OER) to help faculty create high-quality, zero-cost, and accessible course materials. Supported by the Southern Regional Education Board (SREB) Open Education Capacity Building Grant, Hillsborough is developing Z-degree pathways through paid faculty opportunities, targeted training for academic advisors, and tools to track and expand OER adoption. This session shares lessons learned, explores AI-OER implementation strategies, and presents scalable, adaptable models for institutions in Alabama and beyond
A Psychometric Evaluation of the Intentionality Bias Task
Full text linkIntentionality Bias Task (IBT) provides quick and easy assessment of the tendency to overattribute intentionality to the behaviors of others. The IBT has been used repeatedly in research that has attempted to connect intentionality bias to a wide range of disorders and socio-emotional abilities, including schizophrenia spectrum disorder, autism spectrum disorder, and cognitive empathy. To date, however, there has been no systematic examination of the IBT’s psychometric properties. The present study attempts to fill this gap by testing whether the IBT possesses a reliable factor structure. Specifically, the 34 items of the IBT were written to reflect two types of behaviors: prototypically intentional behaviors and prototypically accidental behaviors. This two-factor structure was first tested using confirmatory factor analysis (CFA), which examined factor loadings, modification indices, and item-total correlations. Despite revisions, model fit was found to be less than acceptable. Following this, an exploratory factor analysis was used to identify items that were cross-loading, failing to load on either factor, other otherwise impairing model fit. Again despite revisions, model fit was found to be less than acceptable. The two-factor model was abandoned in favor of a one-factor model containing solely the prototypically accidental (PA) items. While this one-factor model achieved acceptable model fit, the model failed to replicate in a separate sample.
Keywords: Intentionality bias, Intentionality Bias Task, Evelyn Rosset, ICED model, NICED mode