The description of games. by Sadaf Sepasgozar Sarkhosh (20436143)

Comparison of Mean Absolute Error (MAE) in Millimeters as a Function of Kernel Size. by Liu Liu (512237)

Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Graphical representation of the optimization process in machine learning, focusing on the adjustment of weights during gradient descent. by Liu Liu (512237)

Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. …”

K-means results. by Fei Zhang (85787)

“…NFS accounts for the majority of game time but decreases as the game progresses. The LightGBM analysis highlighted the importance ranking of key performance indicators (KPIs) across different segments and revealed differences in the importance of these indicators within each segment. …”

Feature importance result of SHAP. by Fei Zhang (85787)

“…NFS accounts for the majority of game time but decreases as the game progresses. The LightGBM analysis highlighted the importance ranking of key performance indicators (KPIs) across different segments and revealed differences in the importance of these indicators within each segment. …”

Definition of variables. by Fei Zhang (85787)

“…NFS accounts for the majority of game time but decreases as the game progresses. The LightGBM analysis highlighted the importance ranking of key performance indicators (KPIs) across different segments and revealed differences in the importance of these indicators within each segment. …”

Result of random forest. by Fei Zhang (85787)

“…NFS accounts for the majority of game time but decreases as the game progresses. The LightGBM analysis highlighted the importance ranking of key performance indicators (KPIs) across different segments and revealed differences in the importance of these indicators within each segment. …”

AI KRegression by CHIN-CHENG CHU (20718575)

Estimated marginal mean (± SE) age group differences in the average time on ball performed by professional soccer players on a match day for each position. by Emily Escreet (20552634)

Presentation 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Data Sheet 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Estimated marginal mean values representative of the average time on ball and the relative frequency of ball touches and releases per minute of match duration, performed by profess... by Emily Escreet (20552634)

Estimated marginal mean values representative of the inter-positional differences in average time on ball and the relative frequency of ball touches and releases per minute of matc... by Emily Escreet (20552634)

Tree cover limits occupancy of a declining game bird by Bradley Kubecka (7387181)

“…Probability of bobwhite occupancy decreased as canopy cover increased (β<em>_Tree</em> = -0.74, 95% CrI: -1.29 – -0.28); occupancy was over 19 times higher when canopy cover was 44% versus the mean observed value of 80.8% (range: 38–96%). …”

Interaction plot with 95% confidence intervals generated from the GAM regression model 1 in Table 2 examining initial ED SBP and management group interactions. by Randeep S. Jawa (20489181)

GPT-4 results in decreased error rate for all tasks with increasing complexity when compared to GPT-3.5-turbo. by Jacqueline A. Jansen (14894276)

Data Sheet 1_Serious gaming as an experiential learning tool: exploring the human–water perspectives in the case of Mt. Kenya water tower.docx by Charles Nduhiu Wamucii (20912792)

“…The Upper Ewaso Ng’iro basin in Kenya was selected as the study area for its complex social-ecological dynamics, characterized by the interplay of climatic variability, competing water demands, and governance challenges that shape water resource management. Through five game sessions, participants’ perspectives were assessed at three points in time: pre-game, post-game, and post-post-game, using the Q-method. …”