Simulating Methylamine Using a Symmetry-Adapted, Qubit Excitation-Based Variational Quantum Eigensolver by Konstantin M. Makushin, Aleksey K. Fedorov

Get full text

Modeling vector control of the asynchronous drive of electric rolling stock auxiliary machines by Yu. M. Kulinich, S. A. Shukharev, V. K. Dukhovnikov, A. V. Gulyaev

“…The developed complex of an asynchronous motor and a vector control system enable to work out various algorithms for improving the energy efficiency of the operation of asynchronous auxiliary machines of an electric locomotive by applying the proposed algorithm for choosing the optimal value of the rotor flux linkage. …”
Get full text

Analysis of the state of geometrization development and digital modeling in open-pit mining enterprises by M.S. Kunytska, D.S. Polishchyk, O.V. Shapochnikov

“…The article is devoted to the study of modern technologies of geometrization and digital modeling at open-pit mining enterprises. The relevance of the work is due to the requirements for optimizing mining processes, ensuring labor safety and increasing economic efficiency in the exploitation of deposits. …”
Get full text

Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…Initially, the SIMDP-EDLIoT approach uses linear scaling normalization (LSN) to ensure that the input data is scaled appropriately. Besides, the Improved Osprey Optimization Algorithm (IOOA)-based feature selection is employed to classify the most relevant features, enhancing the efficiency of the system by reducing dimensionality. …”
Get full text

Characterizing Wake Behavior of Adaptive Aerodynamic Structures Using Reduced-Order Models by Kyan Sadeghilari, Aditya Atre, John Hall

“…Hence, the development of better wake models is critical for better turbine design and controls. …”
Get full text

Research on Financial Stock Market Prediction Based on the Hidden Quantum Markov Model by Xingyao Song, Wenyu Chen, Junyi Lu

“…Experimental results demonstrate that the proposed quantum model outperforms classical algorithmic models in handling higher complexity, achieving improved efficiency, reduced computation time, and superior predictive performance. …”
Get full text

Effectiveness of machine learning models in diagnosis of heart disease: a comparative study by Waleed Alsabhan, Abdullah Alfadhly

“…An extensive array of preprocessing techniques is thoroughly examined in order to optimize the predictive models’ quality and performance. …”
Get full text

Multi-objective optimization of custom implant abutment design for enhanced bone remodeling in single-crown implants using 3D finite element analysis by Pongsakorn Poovarodom, Chaiy Rungsiyakull, Jarupol Suriyawanakul, Qing Li, Keiichi Sasaki, Nobuhiro Yoda, Pimduen Rungsiyakull

“…In conclusion, the depth and taper have a significant effect on bone remodeling. This optimized model significantly improves bone density uniformity.…”
Get full text

Optimasi Algoritma Support Vector Machine Berbasis Kernel Radial Basis Function (RBF) Menggunakan Metode Particle Swarm Optimization Untuk Analisis Sentimen by Cucun Very Angkoso, Khozainul Asror, Ari Kusumaningsih, Andi Kurniawan Nugroho

“…These reviews are an important source of information for application developers to understand user perceptions, identify problems, and improve service quality. The study investigates the effectiveness of the Particle Swarm Optimization (PSO) method for balanced and unbalanced datasets and how well it improves sentiment analysis accuracy when applied to the Support Vector Machine (SVM) algorithm when using Radial Basis Function (RBF) kernel. …”
Get full text

Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography by Arpitha Ravi, Philipp Bernhardt, Mathis Hoffmann, Florian Kordon, Siming Bayer, Stephan Achenbach, Andreas Maier

“…This model has the potential to streamline clinical workflows, improve diagnostic accuracy, and enhance safety for both patients and operators.…”
Get full text

Robust InceptionV3 with Novel EYENET Weights for Di-EYENET Ocular Surface Imaging Dataset: Integrating Chain Foraging and Cyclone Aging Techniques by Muhammad Ahmad Khan, Saif Ur Rehman Khan, Hafeez Ur Rehman, Suliman Aladhadh, Ding Lin

“…This research highlights the potential of nature-inspired optimization algorithms and tailored datasets to enhance AI model robustness and adaptability in the context of medical disease diagnosis, particularly in the field of diabetic eye disease.…”
Get full text

Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…Cross-validation and feature selection methods were used to optimize model performance and identify key variables that most significantly impact soil resistivity. …”
Get full text

A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…The proposed framework offers improved accuracy, precision, and computational efficiency compared to state-of-the-art models. …”
Get full text

Observer-based finite-time event-triggered secure control for fuzzy implicit systems against deception attacks: A single-link flexible joint robotic application by M. Kchaou, L. Ladhar, M. Omri, R. Abbassi, H. Jerbi

“…Furthermore, the Gray Wolf Optimization (GWO) algorithm is employed alongside linear matrix inequality techniques to optimize the gains of both the controller and the observer. …”
Get full text

Revealing the Driving Factors of Household Energy Consumption in High-Density Residential Areas of Beijing Based on Explainable Machine Learning by Zizhuo Qi, Lu Zhang, Xin Yang, Yanxia Zhao

“…Data were collected through field surveys, questionnaires, and interviews, covering 16 influencing factors across household, building, environment, and transportation categories. A hyperparameter-optimized ensemble model (XGBoost, RF, GBDT) was employed, with XGBoost combined with genetic algorithm tuning performing best. …”
Get full text

Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer by Li Zhang, Qinglin Du, Mengyi Shen, Xin He, Dingyi Zhang, Xiaohua Huang

“…The Shapley Additive Explanation (SHAP) algorithm was employed to explain the optimal model, and the AUC was used to assess the model’s performance. …”
Get full text

A nonlinear dynamic hysteresis model and dynamic performance of the piezoelectric ring bending actuator by Yuesong Li, Bang Wang

“…Second, an improved model of the piezoelectric ring bending actuator was developed based on the Bouc–Wen model, and its parameters were identified by the particle swarm optimization algorithm. …”
Get full text

Strategic Power Flow-Stackelberg Dynamics for Minimizing Transmission Losses in Peer-to-Peer Trading by K. V. Biji Varghese, Dattatraya N. Gaonkar

“…In networked microgrids, some units may have surplus energy while others experience deficits, creating a buyer-seller trade dynamic. This dynamic is modeled using a multi-leader, multi-follower Stackelberg game. …”
Get full text

Enhanced load frequency regulation in microgrids with renewable energy sources and electric vehicles by Imran Khan, Suheel Abdullah Malik, Amil Daraz, Baitullah Bareer

“…Simulation results show that the (I-P) cascaded PDN controller significantly outperforms existing controllers, such as PID, and PI-based models, by reducing frequency deviations, improving settling time, and minimizing overshoot and error indices. …”
Get full text

A model predictive control method for directional borehole trajectories in underground coal mines by Hao LI, Ningping YAO, Chengda LU, Jinbao ZHANG, Hongchao WEI, Jiajun WU, Jinyu LI

“…The steady-state errors of the prediction model were reduced using feedback correction. Furthermore, this study designed a model predictive controller with functions of predictive modeling, rolling optimization, and feedback correction. …”
Get full text