Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review by Muhammad Sabo Yahaya, Ahmad Sobri B. Hashim, Abdullateef Oluwagbemiga Balogun, Aminu Aminu Muazu, Fatima Sabo Usman, Dahiru Adamu Aliyu, Abdullahi Uwaisu Muhammad

“…These methods consistently outperform traditional techniques by reducing test suite sizes and enhancing fault detection capabilities. The findings underscore the growing adoption of the one-test-at-a-time (OTAT) approach over the one-parameter-at-a-time (OPAT) approach and identify key challenges in scalability, hyperparameter tuning, and constraint handling, highlighting the need for hybrid strategies and adaptive optimization techniques. …”
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Beyond N-Grams: Enhancing String Kernels With Transformer-Guided Semantic Insights by Nazar Zaki, Reem Alderei, Mahra Alketbi, Alia Alkaabi, Fatima Alneyadi, Nadeen Zaki

“…Comprehensive hyperparameter optimization further solidifies our methods’ effectiveness and practical applicability. …”
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Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…The novelty of the work is to maximize the performance of the model by using methods including the isolation forest for anomaly detection and the tree-structured Parzen estimator for hyperparameter fine-tuning. …”
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The Discriminants of Long and Short Duration Failures in Fulfillment Sortation Equipment: A Machine Learning Approach by Abed Mutemi, Fernando Bacao

“…Under a variety of hyperparameter configurations, we test and compare the outcomes of eight different machine learning classification algorithms, seven individual classifiers, and a stacked ensemble. …”
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Simplifying Masked Image Modeling With Symmetric Masking and Contrastive Learning by Khanh-Binh Nguyen, Chae Jung Park

“…While prior approaches have demonstrated strong performance, they typically rely on random masking strategies and require extensive hyperparameter tuning—particularly in searching for optimal masking ratios—leading to increased training cost and reduced generalizability. …”
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Identification of NAPL Contamination Occurrence States in Low-Permeability Sites Using UNet Segmentation and Electrical Resistivity Tomography by Mengwen Gao, Yu Xiao, Xiaolei Zhang

“…This technological breakthrough overcomes the high-cost and low-efficiency limitations of traditional borehole sampling, providing a high-precision, non-destructive intelligent detection solution for contaminated site remediation.…”
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Analyzing social psychological impact on emotional expression through peer communication using crayfish optimization algorithm with deep learning model by Umkalthoom Alzubaidi

“…Finally, the crayfish optimization algorithm (COA) adjusts the VAE model’s hyperparameter values, improving classification. The efficiency of the SPIEEPC-COADL model is examined using emotion detection from the text dataset. …”
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Evaluation of predictive maintenance efficiency with the comparison of machine learning models in machining production process in brake industry by Can Aydın, Burak Evrentuğ

“…Regular maintenance of machines and early detection of faults play a critical role in ensuring uninterrupted production and business continuity. …”
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Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm by K. Gopalakrishnan, R. Sivaraj, M. Vijayakumar

“…Deep learning (DL) based object detection model has been carried out in numerous applications. …”
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A Convolutional Neural Network for Early Supraventricular Arrhythmia Identification by Emilio J. Ochoa, Luis C. Revilla

“…A binary cross-entropy loss function, Adam optimizer, and a batch size of 128 were obtained after a hyperparameter tuning. As a training-validation methodology, a 50-fold cross-validation technique was used. …”
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Ransomware Family Attribution With ML: A Comprehensive Evaluation of Datasets Quality, Models Comparison, and a Simulated Deployment by Emilio Rios-Ochoa, Jesus Arturo Perez-Diaz, Enrique Garcia-Ceja, Gerardo Rodriguez-Hernandez

“…We then train four traditional Machine Learning (ML) and two Deep Learning (DL) models, applying consistent preprocessing and hyperparameter tuning for fair comparisons. Next, we propose a real-time detection architecture in a Windows 10 virtual environment to deploy the models against live ransomware. …”
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Integrating Explainable Artificial Intelligence With Advanced Deep Learning Model for Crowd Density Estimation in Real-World Surveillance Systems by Sultan Refa Alotaibi, Hanan Abdullah Mengash, Mohammed Maray, Faiz Abdullah Alotaibi, Abdulwhab Alkharashi, Ahmad A. Alzahrani, Moneerah Alotaibi, Mrim M. Alnfiai

“…Crowd Density Detection in Smart Video Surveillance involves advanced computer vision (CV) techniques to improve the efficiency and accuracy of crowd monitoring. …”
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Enhancing Dermatological Diagnosis Through Medical Image Analysis: How Effective Is YOLO11 Compared to Leading CNN Models? by Rakib Ahammed Diptho, Sarnali Basak

“…The expedition performance of YOLO11 signifies a promising trajectory in the development of highly accurate skin disease detection models. Our analysis not only highlights the strengths and weaknesses of the model but also underscores the rapid development of deep learning techniques in medical imaging.…”
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Nuclei segmentation and classification from histopathology images using federated learning for end-edge platform. by Anjir Ahmed Chowdhury, S M Hasan Mahmud, Md Palash Uddin, Seifedine Kadry, Jung-Yeon Kim, Yunyoung Nam

“…Accurate nuclei segmentation and classification in histology images are critical for cancer detection but remain challenging due to color inconsistency, blurry boundaries, and overlapping nuclei. …”
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Heart Disease Prediction Using a Hybrid Feature Selection and Ensemble Learning Approach by Isha Gupta, Anu Bajaj, Manav Malhotra, Vikas Sharma, Ajith Abraham

“…This approach also integrated GA for hyperparameter tuning, enhancing predictive accuracy. …”
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Ensemble Voting Method for Phonocardiogram Heart Signal Classification Using FFT Features by Adisaputra Zidha Noorizki, Heri Pratikno, Weny Indah Kusumawati

“…Hyperparameter tuning, particularly learning rate adjustment, is applied to optimize the performance of the models. …”
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Enhancing cybersecurity via attribute reduction with deep learning model for false data injection attack recognition by Faheed A.F. Alrslani, Manal Abdullah Alohali, Mohammed Aljebreen, Hamed Alqahtani, Asma Alshuhail, Menwa Alshammeri, Wafa Sulaiman Almukadi

“…The primary goal of the ARDL-FDIAR technique is to improve security via the FDIA detection process. The ARDL-FDIAR technique uses Z-score normalization to scale the input data. …”
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Multimodal rapid identification of growth stages and discrimination of growth status for Morchella by Ning Jia, Chunjun Zheng

“…This strategy effectively achieves the goals of object detection and instance segmentation, and thus we have accurately evaluated the growth status of Morchella in the later stages of mulberry, young mushroom, and mature. …”
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ECG-based transfer learning for cardiovascular disease: A scoping review by Sharifah Noor Masidayu Sayed Ismail, Siti Fatimah Abdul Razak, Nor Azlina Ab Aziz

“…It is valuable for the early detection of cardiovascular disease (CVD). Advancements in medical diagnosis using artificial intelligence have popularised transfer learning among researchers in machine learning and deep learning. …”
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Integrating Machine Learning Algorithms: A Hybrid Model for Lung Cancer Outcome Improvement by Pradnyawant M. Gote, Praveen Kumar, Hemant Kumar, Prateek Verma, Moses Makuei Jiet

“…It remains one of the leading causes of cancer-related deaths worldwide, often detected at advanced stages due to the lack of early symptoms. …”
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