Results of the preprocessing techniques and valid constraints over the linear relaxation of the 3IFv2. حسب Alejandro Arenas-Vasco (19797133)

Preprocessing techniques. حسب Shweta Sharma (41033)

Example of preprocessed image. حسب Jiexiang Yang (19980594)

Data acquisition and preprocessing process. حسب Liang Chen (73736)

Design of a comb over a graph. حسب Alejandro Arenas-Vasco (19797133)

Wavelet transform preprocessing results. حسب Chao Tang (10925)

Line plots current over fault type. حسب Zawar Ahmed Khan (22574556)

"…A dataset of triaxial vibrational current data at 0.7 mm bearing and rotor faults at various loads (100W, 200W, and 300W) were considered. For the data preprocessing, we handled with the missing values by interpolation and handle data imbalance fault types with Synthetic Minority Over-sampling Technique (SMOTE). …"

Summary of data before and after preprocessing. حسب Riaz Ud Din (21101290)

X-CRISP: Domain-Adaptable and Interpretable CRISPR Repair Outcome Prediction - Preprocessed CRISPR repair outcomes and train/test target splits حسب Colm Seale (21499823)

Accuracy over selected features. حسب Shaista Khanam (21387548)

"…This study introduces an advanced framework for anomaly recognition in surveillance, leveraging deep learning to address these challenges and achieve significant improvements over current techniques. The framework begins with preprocessing input images using histogram equalization to enhance feature visibility. …"

Boxplot of the box-counting method to obtain the fractal dimension over each urban state variable’s binarized (info/no-info) image. حسب Lady Adriana Hoyos-Rincón (21417887)

Changes in total force on the left and right feet over time for Parkinson’s patients and the healthy control group revealed that Parkinson’s patients tend to exhibit longer duratio... حسب Hua Huo (1818133)

Supplementary material for the paper "Demonstration the importance of pre-processing the text fields of bibliometric records to identify promising research tasks. Case study of Sco... حسب Boris Chigarev (6474086)

CTWA method related data حسب Yang YuTong (22192153)

"…These datasets can be used to develop, benchmark, and validate intrusion detection models, especially in incremental learning settings where new attack classes are introduced over time.</p><p dir="ltr"><b>Usage:</b></p><ul><li>Training and testing of IoT intrusion detection models</li><li>Research on class incremental learning and continual learning</li><li>Evaluation of model performance in distinguishing known and unknown attack types</li></ul><p dir="ltr"><b>File Contents:</b></p><ul><li><code>CICIoT2023_preprocessed.csv</code> – Preprocessed CICIoT2023 dataset</li><li><code>BotNetIoT_preprocessed.csv</code> – Preprocessed <code>BotNetIoT</code> dataset</li></ul><p dir="ltr"><b>Potential Applications:</b></p><ul><li>Cybersecurity research in IoT environments</li><li>Development of intelligent intrusion detection systems</li><li>Benchmarking novel machine learning methods in class incremental learning</li></ul><p></p>…"

Issues with automatic and team-based QC. حسب Michael E. Kim (21956727)

Quality controlled, reliable groundwater level data with corresponding specific yield over India حسب K. Satish Kumar (21525779)

Hyperparameter values used in our experiments. حسب Zarin Akter (22794652)

"…We evaluate the proposed DR detection approach on APTOS2019, Messidor-2, and EyePACS datasets, achieving superior performance over state-of-the-art methods. Using MobileViT as the main feature extractor, we reached a remarkable 98.45% accuracy, 98.45% F1-Score, and 98.06% Kappa on the APTOS2019 dataset. …"

<b>Descriptive statistics and PLS calibration models for pol content of sugarcane juice samples extracted using the direct extraction method (DEM) and shredded extraction method (S... حسب Akeme Cyril NJUME (22387990)

"…</p><p><br></p><p dir="ltr">Table S2 Performance of individual PLS calibration models for predicting pol content in sugarcane juice samples extracted using DEM and SEM, measured with a benchtop NIR spectrophotometer</p><p dir="ltr">(EAEF180305_Table_S2.csv)</p><p dir="ltr">DEM: direct extraction method, SEM: shredded extraction method, <i>n</i>: total number of samples, λ: wavelength, nm: nano meter, LV: latent variable, dash (-): the same calibration values of DEM and SEM are represented in SEM and DEM directly below the extraction treatment, 2D: second derivative preprocessed spectra, Cal: calibration, Val: validation, <i>R</i>_cv²: coefficient of determination of cross-validation, ^a<i>SEC</i>: root mean square error of calibration, <i>R</i>_p²: coefficient of determination of prediction, ^b<i>SEP</i>: root mean square error of prediction, %: percentage of pol content in sugarcane juice.…"

Overall flow of the HPDL-MIAIHD approach. حسب Naif Almakayeel (16846021)

"…To increase the efficiency of the EfficientNet method, the hyperparameter tuning process is performed by utilizing the chimp optimizer algorithm (COA) method. …"

Details on database. حسب Naif Almakayeel (16846021)

"…To increase the efficiency of the EfficientNet method, the hyperparameter tuning process is performed by utilizing the chimp optimizer algorithm (COA) method. …"