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

Subjects:

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. …”

Average ca for HT-based features extracted from 2.4-second time segments using classification methods. by Ebru Ergün (21395498)

Average CA for HT, FWHT, BP, and SF-based features extracted from 2.4-second time segments using the k-NN classifier. by Ebru Ergün (21395498)

Trainable parameters for different algorithms. by Anwar Hossain Efat (19942283)

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. …”

Confusion matrix for multiclass classification. by Ebru Ergün (21395498)

“…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …”

General flow chart of the proposed method. by Ebru Ergün (21395498)

“…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …”

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. …”

Data_Sheet_1_Hierarchical multi-class Alzheimer’s disease diagnostic framework using imaging and clinical features.docx by Yao Qin (385509)

“…The combination of selected imaging features and clinical variables improved the multi-class performance using the AdaBoost algorithm, with overall accuracy rates of 0.877 in the temporal validation set. …”

Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

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. …”

Category range of secondary indicators. by Yixuan Lu (9987980)

“…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”

Diagram of ANP network structure. by Yixuan Lu (9987980)

“…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”

Comparison of methodologies in scheme selection. by Yixuan Lu (9987980)

“…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”

Judgment matrix of control layer U. by Yixuan Lu (9987980)

“…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”