A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

Algorithm testing. by Ziad M. Ali (12516532)

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TB screening and diagnostic algorithm. by Arangba S (21656068)

Convergence curves of the investigated algorithms. by Ziad M. Ali (12516532)

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CSSI Elements: Multi-GPU and Network Modeling and Simulation in SST by Kishwar Ahmed (21792083)

, MSE, and MAE of the optimised algorithms. by Itxasne Antúnez Sáenz (22794696)

Accuracy and average dots covered for difficulty level 11 using gradient descent to find the optimal solution. by Tarun Khajuria (12117309)

Analysis of elements of emergency resource scheduling model in chemical industry park. by Yuhang Wang (332111)

Multi-material topology optimization using scaled boundary finite element method by Mohammed Saif Zamiruddin Siddiqui (22384884)

“…<p>This work introduces the use of Scaled Boundary Finite Element Method (SBFEM) in Multi-Material Topology Optimization (MMTO) problems, which is new in the literature. …”

Generation and filling algorithm of macro geometry of cathode carbon block. by Chenglong Gong (20629836)

M3C2 algorithm diagram. by Xiaowei Li (620087)

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Overview of different metaheuristic algorithms used in PV parameter estimation and their corresponding full names and acronyms. by Ziad M. Ali (12516532)

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Signal strength of adverse events that are unexpected findings of Relugolix (Orgovyx^®)-related adverse events at the preferred term (PT) level. by Ruibo Li (2063167)

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Clinical use algorithm. by Chibuike K. Uwakwe (22655742)

Performance of machine learning algorithms. by Wenxue Liu (6877754)

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... by Zhao Li (300229)

Filtered Labels after applying the data preparation algorithms. by Tanjim Taharat Aurpa (11250554)

Data Sheet 1_Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs.pdf by Thiago Fellipe Ortiz de Camargo (19460818)

“…</p>Results<p>In the internal validation, the Lung Abnormality and Tuberculosis models achieved an AUC of 0.94, while the Radiological Findings model yielded a mean AUC of 0.84. During the external validation, utilizing the ground truth generated by board-certified thoracic radiologists, the algorithm achieved better sensitivity in 6 out of 11 classes than physicians with varying experience levels. …”

Dataset state after applying our data preparation algorithm. by Tanjim Taharat Aurpa (11250554)