Damping damper test bench. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Step signal response curve. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Boundary selection strategy one. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Sinusoidal signal response curve. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Step signal response curve. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

DBO-DO-RAC tuning parameters. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Main parameters of the mode l. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Sinusoidal signal error curve. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Sinusoidal signal error curve. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Boundary selection strategy two. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

S1 Data - by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Step signal error curve. by Xiangfei Tao (20775636)

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”

Simulink model of DBO-DO-RAC controller. by Xiangfei Tao (20775636)

Example steps for checking the input movie data. by Yukako Yamane (9034133)

“…Challenges in analysis includes 1) ensuring data quality of original and processed data at each step, 2) selecting optimal algorithms and their parameters from numerous options, each with its own pros and cons, by implementing or installing them manually, 3) systematically recording each analysis step for reproducibility, and 4) adopting standard data formats for data sharing and meta-analyses. …”

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

Real-world networks used in this study. by Minhyuk Park (10783684)

“…Surprisingly, we find that five different community detection methods–the Leiden algorithm optimizing the Constant Potts Model, the Leiden algorithm optimizing modularity, Infomap, Markov Cluster (MCL), and Iterative k-core (IKC)–identify communities that fail even a mild requirement for well-connectedness. …”

Software: Learning zero-cost portfolio selection with pattern matching by Tim Gebbie (8064947)

“…A quadratic approximation is used to find the log-optimal portfolio using T+1 expected return subsequent to the pattern matching times T for each k and ell to find H(K,L,CI;T) and SH(K,L,CI;T) for each K-tuple L value and cluster CI. …”

Parameters of stimuli used in the study. by Elnaz Nemati (21402730)

“…The model suggests that an excessive emphasis on prior knowledge prolongs the stabilization time for motion detection, whereas an optimal integration of prior expectations enhances detection accuracy and efficiency by preventing excessive disturbances due to noise. …”

Testing the proposed ACB-XDE framework. by Riaz Ud Din (21101290)

“…<div><p>Forecasting speculative stock prices is essential for effective investment risk management and requires innovative algorithms. However, the speculative nature, volatility, and complex sequential dependencies within financial markets present inherent challenges that necessitate advanced techniques. …”

Z-score analysis for outlier detection. by Riaz Ud Din (21101290)

“…<div><p>Forecasting speculative stock prices is essential for effective investment risk management and requires innovative algorithms. However, the speculative nature, volatility, and complex sequential dependencies within financial markets present inherent challenges that necessitate advanced techniques. …”