Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

Subjects:

Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases by Jina Lee (3138492)

“…To validate the accuracy of the model, the results obtained from the proposed algorithm were compared to experimental data for 37 binary aqueous mixture systems covering properties such as density, heat capacity, viscosity, and thermal conductivity. …”

Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases by Jina Lee (3138492)

“…To validate the accuracy of the model, the results obtained from the proposed algorithm were compared to experimental data for 37 binary aqueous mixture systems covering properties such as density, heat capacity, viscosity, and thermal conductivity. …”

Event-driven data flow processing. by Yixian Wen (12201388)

“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”

MARGO workflow, tracking algorithm, and sample behavioral box. by Zach Werkhoven (6473165)

UK Biobank data wrangling statistics and results. by Simeone Marino (81051)

Flow diagram of the proposed model. by Uğur Ejder (22683228)

“…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression–Artificial Bee Colony (LR–ABC) framework can enhance predictive performance in in vitro fertilization (IVF) outcomes while producing interpretable, hypothesis-driven associations with nutritional and pharmaceutical supplement use. …”

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx by Çaǧlar Çaǧlayan (12253934)

“…</p>Materials and Methods<p>Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. …”

Analysis of geo-spatiotemporal data using machine learning algorithms and reliability enhancement for urbanization decision support by Kwame O. Hackman (9289505)

“…Two classification algorithms – random forest (RF) and support vector machines (SVM) – were used to produce binary (built-up / non-built up) maps for all years within the temporal span. …”

Cell classification. by Adam L. Tyson (10892822)

Confusion matrix. by Yixian Wen (12201388)

“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”

Parameter settings. by Yixian Wen (12201388)

“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”

Dynamic resource allocation process. by Yixian Wen (12201388)

“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…In this direction, the option of estimating the statistics of the model directly from the training image (performing a refined pattern search instead of simulating data) is a very promising.<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

“…RSEE projects heterogeneous input data into an exertion-conditioned latent space, aligning model predictions with observed physiological variance and mitigating false positives by explicitly modeling the overlap between athletic remodeling and subclinical pathology.…”

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…<p dir="ltr">The first algorithm for segmentation and localization (see PathOlOgics_script_1; segment & localize using a pen) relied on manually tracing the borders of each cell using a digital pen tool on a big touchscreen display showing source images/patches. …”