Policy-Based Reinforcement Learning Approach in Imperfect Information Card Game by Kamil Chrustowski, Piotr Duch

“…Games provide an excellent testing ground for machine learning and artificial intelligence, offering diverse environments with strategic challenges and complex decision-making scenarios. …”
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A Custom-Developed Device for Testing Tensile Strength and Elasticity of Vascular and Intestinal Tissue Samples for Anastomosis Regeneration Research by Zoltan Attila Godo, Laszlo Adam Fazekas, Gergo Fritsch, Balazs Szabo, Norbert Nemeth

“…One of the most interesting parameter groups is related to the biomechanical properties of the anastomoses. …”
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On the Utilization of Emoji Encoding and Data Preprocessing with a Combined CNN-LSTM Framework for Arabic Sentiment Analysis by Hussam Alawneh, Ahmad Hasasneh, Mohammed Maree

“…Furthermore, the Keras tuner optimized the CNN-LSTM parameters during the 5-fold cross-validation process. …”
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ML: Generalized Additive Model for Spectrum Sensing in Nakagami-<italic>m</italic> Fading Channel With Complex Generalized Gaussian Distribution Noise by Md. Tofail Ahmed, Mousumi Haque, Yosuke Sugiura, Tetsuya Shimamura

“…Deep learning (DL) and machine learning (ML) are trending approaches to enhance the spectrum sensing performance. …”
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Unsupervised surface water mapping with airborne LiDAR data by leveraging physical properties of water by Hunsoo Song, Jinha Jung

“…Traditional methods require the use of either training procedures or the repetitive tuning of site-specific parameters, which present hurdles to automated mapping and introduce biases tied to training data and parameters. …”
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Harnessing feature pruning with optimal deep learning based DDoS cyberattack detection on IoT environment by Eunmok Yang, Sooyong Jeong, Changho Seo

“…Meanwhile, DDoS attacks are recognized using a sparse denoising autoencoder (SDAE) model. Furthermore, the parameter tuning of the SDAE classifier is accomplished by utilizing the Fish Migration Optimizer (FMO) technique. …”
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Sky Temperature Forecasting in Djibouti: An Integrated Approach Using Measured Climate Data and Artificial Neural Networks by Hamda Abdi, Abdou Idris, Anh Dung Tran Le

“…To correctly account for building energy performance, radiative cooling potential, and other technical considerations, it is essential to evaluate sky temperature. It is an important parameter for the weather files used by energy building simulation software for calculating the longwave radiation heat exchange between exterior surfaces and the sky. …”
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3D Finite Element Analysis in Drilling of AA7075 Reinforced with Nano Silicon Carbide Particles by C. Prakash, J. Prakash

“…In addition, a 3D Finite Element Model (3D FEM) was developed to simulate the drilling process for understanding the influence of machining parameters on critical thrust forces, chip formation, chip morphology, stress and hole quality. …”
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A Review of Gait Analysis Using Gyroscopes and Inertial Measurement Units by Sheng Lin, Kerrie Evans, Dean Hartley, Scott Morrison, Stuart McDonald, Martin Veidt, Gui Wang

“…Wearable sensors are used in gait analysis to obtain spatiotemporal parameters, with gait events serving as critical markers for foot and lower limb movement. …”
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Comparative Study and Real-World Validation of Vertical Load Estimation Techniques for Intelligent Tire Systems by Ti Wu, Xiaolong Zhang, Dong Wang, Weigong Zhang, Deng Pan, Liang Tao

“…Vertical load prediction algorithms are developed using Support Vector Machine (SVM) and linear regression, considering variables like contact length, vehicle speed, and tire pressure. …”
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Crow Search Algorithm for MEMS Gyroscope Temperature Drift Signal and Processing for Denoising by Xichen Wang, Huiliang Cao, Xiaomin Duan

“…First, the signal was decomposed by variational mode decomposition for optimization of crow search algorithm (CSA-VMD) method. The parameters required by the VMD method (penalty parameter α and decomposition number K) are given by the crow search algorithm, and then the signal is decomposed into the superposition of multiple subsignals, called intrinsic mode functions (IMFs). …”
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Square-root lasso under correlated regressors: Tight statistical analysis with a wireless communications application by Ayed M. Alrashdi, Masad A. Alrasheedi

“…The expressions and insights obtained from this study can be used to optimally choose the penalization parameter of the sqrt-lasso. By applying these results, one can make informed decisions about performance and fine-tuning the sqrt-lasso, considering the presence of correlated regressors in a high-dimensional context.…”
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A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning. by Fayaz Hassan, Zafi Sherhan Syed, Aftab Ahmed Memon, Saad Said Alqahtany, Nadeem Ahmed, Mana Saleh Al Reshan, Yousef Asiri, Asadullah Shaikh

“…The experimental results using CICIDS2017 dataset demonstrate that proposed hybrid model performs well not only in terms of classification performance but also yields trained models that have a low parameter count and model size. Thus, the proposed low-complexity models can be used for intrusion detection in VANET scenario.…”
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Statistical thermal study of ternary hybrid nanofluid flow in coaxial cylinder: artificial neural network approach by s Manjunatha, Khalil Ur Rehman, Wasfi Shatanawi, Tanuja T N

“…Additionally, the heat transfer rate is analysed by using backpropagated Levenberg-Marquardt Machine learning algorithm. Further, the correlation between the parameter on the rate of heat transfer is analysed by using Mean square error and regression graphs. …”
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Pattern Recognition in Urban Maps Based on Graph Structures by Xiaomin Lu, Zhiyi Zhang, Haoran Song, Haowen Yan

“…Current pattern recognition methods for map groups primarily fall into two categories: machine learning-based approaches and traditional methods. …”
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Application of neural architecture search in lithology identification by Yuhao Zhang, Hanmin Xiao, Meng Du, Qingjie Liu, Jingwei Tao, Yongcheng Luo, Li Peng, Jianbo Tan

“…Conventional methods that rely on empirical correlations or elementary machine learning approaches frequently produce suboptimal outcomes under complex, multidimensional subsurface conditions. …”
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Prediction of Settlement Due to Shield TBM Tunneling Based on Three-Dimensional Numerical Analysis by Ji-Seok Yun, Han-Kyu Yoo, Sung-Pil Hwang, Woo-Seok Kim, Han-Eol Kim

“…The Tunnel Boring Machine (TBM) method has gained attention as an eco-friendly tunneling technique, effectively reducing noise, vibration, and carbon emissions compared to conventional blasting methods. …”
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Development of a Mobile-Based Application for Classifying Caladium Plants Using the CNN Algorithm by Rudy Chandra, Tegar Arifin Prasetyo, Heni Ernita Lumbangaol, Veny Siahaan, Johan Immanuel Sianipar

“…The best model is found with the parameter epoch 100, learning rate 0.001, and batch size 64. …”
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Optimal deep learning based vehicle detection and classification using chaotic equilibrium optimization algorithm in remote sensing imagery by Youseef Alotaibi, Krishnaraj Nagappan, Tamilvizhi Thanarajan, Surendran Rajendran

“…In addition, CEOA based hyperparameter optimizer is designed for the parameter tuning of the ResNet model. For the vehicle classification process, the VDTC-CEOADL technique exploits the attention-based long-short-term memory (ALSTM) mod-el. …”
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Effect of the addition of silver nanoparticles on the mechanical properties of an orthodontic adhesive by Marco Sánchez-Tito, Lidia Yileng Tay

“…The shear bond strength was recorded using a universal testing machine, and the adhesive remnant index was evaluated using a stereomicroscope. …”
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