Model’s measure methods. by Songsong Wang (8088293)

“…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”

(A) PPI network of Co-genes. (B-D) Three blue, green, and red gene clusters were obtained using k-means for Co-genes. (E) Processing PPI data for Co-genes using Cytoscape. (F) Analyzing PPI data for Co-genes using the Degree algorithm.... by Qingcong Zheng (11169094)

“…(B-D) Three blue, green, and red gene clusters were obtained using k-means for Co-genes. (E) Processing PPI data for Co-genes using Cytoscape. (F) Analyzing PPI data for Co-genes using the Degree algorithm. …”

Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. by Spencer Caplan (10188380)

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Algorithmic flow chart highlighting a possible path of NGM behavior under parallel-presentation. by Spencer Caplan (10188380)

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Illustrates the structure of the C2F-SimDLKA module. After processing with CBS, the features are first split into two parts: one part is retained without any processing, and the ot... by Xunqian Xu (21261899)

General model performance for different algorithms. by Binghan Xue (21253235)

Histogram showing propensity scores as calculated from the processed data, coloured by whether there was a diagnosis of epilepsy (blue) or not (red). by Ioana Duta (18462981)

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PID controller parameters optimization process. by Hongjun Meng (5031806)

Plant leave disease dataset https://www.kaggle.com/datasets/vipoooool/new-plant-diseases-dataset/data. by Abdullah Sheneamer (19169236)

Ultrafast Hydrogen Detection System Using Vertical Thermal Conduction Structure and Neural Network Prediction Algorithm Based on Sensor Response Process by Ruilin Yang (151028)

“…Here we report an ultrafast (0.4 s) hydrogen detection system based on a wafer-scale fabrication process. It consists of a low power (20.2 mW) hydrogen sensor based on vertical thermal conduction structure and a signal processing circuit introduced with a neural network prediction algorithm based on sensor response process. …”

Ultrafast Hydrogen Detection System Using Vertical Thermal Conduction Structure and Neural Network Prediction Algorithm Based on Sensor Response Process by Ruilin Yang (151028)

“…Here we report an ultrafast (0.4 s) hydrogen detection system based on a wafer-scale fabrication process. It consists of a low power (20.2 mW) hydrogen sensor based on vertical thermal conduction structure and a signal processing circuit introduced with a neural network prediction algorithm based on sensor response process. …”

Comparison between Deep and Machine Learning algorithms (MAE and MSE lower the better) [25]. by Marco Alderighi (7195721)

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Comparison of information on predicting survival outcomes or metastasis of cancer patients using machine learning algorithms in the past. by Jingru Dong (14076094)

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Data construction of the first and last rows in . by Xiang Tian (4369285)

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Datasets for Development of Machine Learning Models in Blue Hydrogen Production Process by William George Davies (21661315)

MD5 signatures from specific regions from a set of files by Paul A. Gagniuc (1818325)

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Values used to describe the groups of species considered in this study. by Valentine Fleuré (12822137)

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Example of the distribution of species abundances within a video. by Valentine Fleuré (12822137)

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Data set presentation. by Wenguang Li (6528113)

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Demonstration of data imbalance. by Wenguang Li (6528113)

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