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

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

الموضوعات: "…crayfish optimization algorithm…"

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

Algorithmic experimental parameter design. حسب 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. …"

Spatial spectrum estimation for three algorithms. حسب 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. …"

Flowchart of DQN algorithm. حسب Jiandong Qiu (20389944)

The run time for each algorithm in seconds. حسب 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. …"

Identification of circadian rhythm-related biomarkers and development of diagnostic models for Crohn’s disease using machine learning algorithms حسب Zhijing Zhao (6569369)

"…Diagnostic models were constructed using machine learning algorithms, and biologic therapy efficacy was predicted with advanced regression techniques. …"

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

Risk element category diagram. حسب 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. …"

Data Sheet 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Data Sheet 1_A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm.pdf حسب Tianli Wang (1438498)

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

الموضوعات:

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

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

Image 2_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Table 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Table 6_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Table 2_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"

Table 4_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.xlsx حسب Benedictor Alexander Nguchu (9984371)

"…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …"