Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

Comparison of different optimization algorithms. by Hang Zhao (143592)

Subjects: “…crayfish optimization algorithm…”

Figures of NEXT STEPS IN THE DEVELOPMENT OF PCA-NN MODEL FOR THE IONOSPHERE: DIFFERENT PARAMETERS, REGIONS, NN ALGORITHMS AND IMPUT PARAMETERS by Sara Garcia (22419613)

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Federated averaging algorithm. by Yan Qin (118276)

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Data Sheet 1_Developing decision support algorithm for hypertension medications for use in a digital therapeutic system.pdf by Jeannie K. Lee (9026981)

“…The decision support algorithm was developed through a literature review of clinical and pharmacokinetic studies and knowledge of the pharmacology of aging (pharmacokinetics and pharmacodynamics). …”

Data Sheet 2_Developing decision support algorithm for hypertension medications for use in a digital therapeutic system.pdf by Jeannie K. Lee (9026981)

“…The decision support algorithm was developed through a literature review of clinical and pharmacokinetic studies and knowledge of the pharmacology of aging (pharmacokinetics and pharmacodynamics). …”

Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

Risk element category diagram. by Yao Hu (3479972)

“…This article extracted features related to risk assessment, such as weather factors, airport facility inspections, and security check results, and conducted qualitative and quantitative analysis on these features to generate a datable risk warning weight table. This article used these data to establish an LSTM model, which trained LSTM to identify potential risks and provide early warning by learning patterns and trends in historical data. …”

Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

Subjects:

Comparison of mass attenuation coefficient calculated by Geant4 simulation and acquired from NIST data. by Dong Hyeok Choi (12562048)

Data for Figs 3–9. by Xiaogang Li (299205)

The structure of FasterNext. by Junjie Lu (160350)

“…<div><p>The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under hardware resource constraints. …”

Data Sheet 1_Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity.docx by Zhi Gao (257044)

“…This study aimed to develop an interpretable machine learning algorithm for the effective prediction of mNGS results in patients with FUO.…”

Technological Fitness and Coherence explanation. Schematic representation of the workings of the Fitness and Complexity algorithm and Coherence diversification. by Matteo Straccamore (15083799)

Scatter diagram of different principal elements. by Jizhong Wang (7441697)

“…<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. …”