The assessment process. by Yuchen Hu (8690178)

Example of a call. by Florencia Bazterrica (22177384)

Design of the diabetes risk prediction process. by Wangyouchen Zhang (21681025)

Box plots of time spent on different stages of the variant calling process versus the corresponding F1-score. by Rumeysa Aslıhan Ertürk (22446835)

Example of the iterative update process of the focus after dimensionality reduction via t-SNE. by Wangyouchen Zhang (21681025)

Assembly process and dynamic instability of microtubules. by Jacopo Zattoni (21702634)

Illustration of the recursive objective space exploration process implemented by the ROSE algorithm. by Ihab Hashem (21156806)

Subjects: “…existing deterministic methods…”

Quantifying clustering between splicing-unaware and SANSARA methods. by Daniil K. Lukyanov (20997755)

Subjects:

Data processing diagram, logs are classified and converted into numerical vectors through Algorithm 1. by Hao Zhang (15339)

DBN-GRU Feature Processing Accuracy Levels. by Heena Kauser.Sk (21387794)

“…The model extracts static features (permissions, API calls, intent filters) and dynamic features (system calls, network activity, inter-process communication) from Android APKs, enabling a comprehensive analysis of application behavior.The proposed model was trained and tested on the Drebin dataset, which includes 129,013 applications (5,560 malware and 123,453 benign).Performance evaluation against NMLA-AMDCEF, MalVulDroid, and LinRegDroid demonstrated that DBN-GRU achieved 98.7% accuracy, 98.5% precision, 98.9% recall, and an AUC of 0.99, outperforming conventional models.In addition, it exhibits faster preprocessing, feature extraction, and malware classification times, making it suitable for real-time deployment.By bridging static and dynamic detection methodologies, the DBN-GRU enhances malware detection capabilities while reducing false positives and computational overhead.These findings confirm the applicability of the proposed model in real-world Android security applications, offering a scalable and high-performance malware detection solution.…”

DBN-GRU feature processing accuracy levels. by Heena Kauser.Sk (21387794)

“…The model extracts static features (permissions, API calls, intent filters) and dynamic features (system calls, network activity, inter-process communication) from Android APKs, enabling a comprehensive analysis of application behavior.The proposed model was trained and tested on the Drebin dataset, which includes 129,013 applications (5,560 malware and 123,453 benign).Performance evaluation against NMLA-AMDCEF, MalVulDroid, and LinRegDroid demonstrated that DBN-GRU achieved 98.7% accuracy, 98.5% precision, 98.9% recall, and an AUC of 0.99, outperforming conventional models.In addition, it exhibits faster preprocessing, feature extraction, and malware classification times, making it suitable for real-time deployment.By bridging static and dynamic detection methodologies, the DBN-GRU enhances malware detection capabilities while reducing false positives and computational overhead.These findings confirm the applicability of the proposed model in real-world Android security applications, offering a scalable and high-performance malware detection solution.…”

Schematic diagram of the complete process of the WES experiment and analysis. by Jinhee Jang (3190629)

The process of predicting duration for new incident. by Amirreza Salehi (20496397)

Representation of the process of seeking and accessing transition-related health care for transmasculine participants. by Venkatesan Chakrapani (295935)

Description of assessments and methods for effectiveness measures for people living with dementia. by Den-Ching A. Lee (11221584)

Performance comparison of state-of-the-art methods on CUB 200_2011 dataset. by Mirza Ahsan Ullah (19959314)

Subjects:

Diagram of the CRFS preprocessing process. by Bo Yu (241082)

Data collection methods. by Nicole Salisbury (20208707)

Pareto front representations obtained by solving the BIOBJ problem using the ROSE algorithm and the NBI algorithm, as well as a visualization of the solution process of the ROSE al... by Ihab Hashem (21156806)

Subjects: “…existing deterministic methods…”

Processing power vs. time required for task completion. by Yousef Sanjalawe (22216626)