Deep learning model for early acute lymphoblastic leukemia detection using microscopic images by Vatsala Anand, Prabhnoor Bachhal, Deepika Koundal, Arvind Dhaka

“…The proposed deep optimized CNN model is tuned using the hyperparameters such as 30 epochs, batch size 32 and optimizers, namely Adam and Adamax. …”
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Extreme Gradient Boosting Regressor Solution for Defy in Drilling of Materials by Sangeetha Elango, Elango Natarajan, Kaviarasan Varadaraju, Ezra Morris Abraham Gnanamuthu, R. Durairaj, Karthikeyan Mohanraj, M. A. Osman

“…The use of prediction model in this scenario is much more appropriate and cost-effective. This research aimed to apply extreme gradient boosting (XGBoost) regressor to develop a drilling prediction model. …”
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Multiclass Classification of Imagined Speech Vowels and Words of Electroencephalography Signals Using Deep Learning by Nrushingh Charan Mahapatra, Prachet Bhuyan

“…Decoding an individual’s imagined speech from nonstationary and nonlinear EEG neural signals is a complex task. Related research work in the field of imagined speech has revealed that imagined speech decoding performance and accuracy require attention to further improve. …”
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Detection and Analysis of Malicious Software Using Machine Learning Models by Selman Hızal, Ahmet Öztürk

“…Our findings highlight the importance of employing advanced ML techniques for enhancing obfuscated malware detection capabilities and provide valuable insights for cybersecurity practitioners and researchers. Future research directions include fine-tuning model hyperparameters, exploring ensemble learning approaches, and expanding evaluation to diverse datasets and real-world scenarios.…”
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A comprehensive deep learning approach to improve enchondroma detection on X-ray images by Ayhan Aydin, Caner Ozcan, Safak Aydın Simsek, Ferhat Say

“…All processes, from preprocessing to identifying pathological regions using object detection systems, underwent rigorous cross-validation and oversight by the research team. After performing various operations and procedural steps, including modifying deep learning architectures and optimizing hyperparameters, enchondroma formation in bone tissue was successfully identified. …”
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SHAP Informed Neural Network by Jarrod Graham, Victor S. Sheng

“…A comprehensive grid search was conducted to optimize the hyperparameters, and performance was assessed using metrics such as test loss, RMSE, R² score, accuracy, and training time. …”
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Advanced machine learning artificial neural network classifier for lithology identification using Bayesian optimization by Saâd Soulaimani, Saâd Soulaimani, Ayoub Soulaimani, Kamal Abdelrahman, Abdelhalim Miftah, Mohammed S. Fnais, Biraj Kanti Mondal

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A digital twin-enabled fog-edge-assisted IoAT framework for Oryza Sativa disease identification and classification by Goluguri N.V. Rajareddy, Kaushik Mishra, Satish Kumar Satti, Gurpreet Singh Chhabra, Kshira Sagar Sahoo, Amir H. Gandomi

“…In response to this critical need, the research introduces a timely detection system that leverages the power of Digital Twin (DT)-enabled Fog computing, integrated with Edge and Cloud Computing (CC), and supported by sensors and advanced technologies. …”
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Fine-tuned deep transfer learning: an effective strategy for the accurate chronic kidney disease classification by Zeshan Aslam Khan, Muhammad Waqar, Hashir Ullah Khan, Naveed Ishtiaq Chaudhary, Abeer TMA Khan, Iqra Ishtiaq, Farrukh Aslam Khan, Muhammad Asif Zahoor Raja

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Kerf geometry prediction and optimization in laser cutting of basalt fiber reinforced polymer composites using decision tree and coati optimization algorithm by Ammar H. Elsheikh, Ninshu Ma, Fadl A. Essa, Mahmoud Khedr, Ahmed Mohamed Mahmoud Ibrahim

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Hybrid model for wind power estimation based on BIGRU network and error discrimination‐correction by Yalong Li, Ye Jin, Yangqing Dan, Wenting Zha

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Parameter-Efficient Adaptation of Large Vision—Language Models for Video Memorability Prediction by Iván Martín-Fernández, Sergio Esteban-Romero, Fernando Fernández-Martínez, Manuel Gil-Martín

“…In light of existing research, we propose a particular methodology that transforms Qwen-VL from a language model to a memorability score regressor. …”
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Predicting Wear Rate and Friction Coefficient of Li₂Si₂O₅ Dental Ceramic Using Optimized Artificial Neural Networks by Marko Pantić, Saša Jovanović, Aleksandar Djordjevic, Suzana Petrović Savić, Milan Radenković, Živče Šarkoćević

“…A genetic algorithm (GA) was used to optimize the ANN’s hyperparameters, improving its ability to model complex, nonlinear relationships between input variables, including normal load and velocity and output properties such as wear rate and friction coefficients. …”
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Human activity recognition algorithms for manual material handling activities by Andreas Sochopoulos, Tommaso Poliero, Jamil Ahmad, Darwin G. Caldwell, Christian Di Natali

“…However, there needs to be more research regarding the identification of diverse lifting styles, which requires appropriate datasets and the proper selection of hyperparameters for the employed classification algorithms. …”
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Predicting contrast sensitivity functions with digital twins by Yukai Zhao, Luis Andres Lesmes, Michael Dorr, Zhong-Lin Lu

“…For each prediction task, we utilized the HBM to compute the joint distribution of CSF hyperparameters and parameters at the population, subject, and test levels. …”
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Deep Learning-Based Portfolio Management: Empirical Study of Listed Shares on the Indonesian Stock Exchange by Grace Citra Dewi, Patrick Villanueva, Sutanto Hidayat, Elysabeth Christy Diandra Selano

“…One algorithm model often used is Deep Learning Long Short Term Memory, which utilizes artificial intelligence (AI) and machine learning technology. This research aims to prove whether the Deep Learning Long Short Term Memory (LSTM) prediction results are close to real prices. …”
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Harnessing Machine Learning for Predictive Analysis of Crop Resistance to Extreme Weather Conditions by Pan Susovan Kumar, Shivaj Ghorpade Bipin

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MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…The RF model exhibited reliable performance across most locations. The research findings offer a practical method for forecasting groundwater levels. …”
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Accurate Rotor Temperature Prediction of Permanent Magnet Synchronous Motor in Electric Vehicles Using a Hybrid RIME-XGBoost Model by Jianzhao Shan, Zhongyuan Che, Fengbin Liu

“…This study provides a new technical solution for temperature management in EVs and offers valuable insights for research in related fields.…”
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Intelligent text similarity assessment using Roberta with integrated chaotic perturbation optimization techniques by Esraa Hassan, Amira Samy Talaat, M. A. Elsabagh

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