Linear B-cell epitope prediction for SARS and COVID-19 vaccine design: Integrating balanced ensemble learning models and resampling strategies by Fatih Gurcan

“…The rebalanced datasets were then used in model building with ensemble classifiers employing Boosting, Bagging, and Balancing strategies. Hyperparameter optimization for the classifiers was conducted using GridSearchCV, while feature selection was performed with the recursive feature elimination (RFE) algorithm. …”
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Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

“…This paper introduces the Heuristic Binary Search, an intelligent search algorithm that efficiently explores the solution space, accommodating arbitrary cost function constraints similar to Finite Control Set, while maintaining a fixed switching frequency. …”
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Building construction crack detection with BCCD YOLO enhanced feature fusion and attention mechanisms by Wenhao Ren, Zuowei Zhong

“…Firstly, this model optimizes the Path Aggregation Network (PAN) by introducing lateral skips and weighted feature fusion mechanisms, improving the multi-scale fusion capability of bare concrete crack features. …”
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Simple and High-Precision Hamiltonian Simulation by Compensating Trotter Error with Linear Combination of Unitary Operations by Pei Zeng, Jinzhao Sun, Liang Jiang, Qi Zhao

“…For the lattice system, the second algorithm can achieve 3 to 4 orders of magnitude higher accuracy with the same gate costs as the optimal Trotter algorithm. …”
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Inhomogeneous Illumination Image Enhancement Under Extremely Low Visibility Condition by Libang Chen, Jinyan Lin, Qihang Bian, Yikun Liu, Jianying Zhou

“…The grayscale banding is eliminated by incorporating a visual optimization strategy based on image gradients. Maximum Histogram Equalization (MHE) is used to achieve high contrast while maintaining fidelity to the original content. …”
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Incremental learning with SVM for multimodal classification of prostatic adenocarcinoma. by José Fernando García Molina, Lei Zheng, Metin Sertdemir, Dietmar J Dinter, Stefan Schönberg, Matthias Rädle

“…We propose a pattern recognition system with an incremental learning ensemble algorithm using support vector machines (SVM) tackling this problem employing multimodal MR images and a texture-based information strategy. …”
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Transformer Fault Diagnosis Based on Knowledge Distillation and Residual Convolutional Neural Networks by Haikun Shang, Yanlei Wei, Shen Zhang

“…Subsequently, the Sparrow Optimization Algorithm (SSA) is applied to optimize the hyperparameters of the ResNet50 model, which is trained on DGA data as the teacher model. …”
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RL-MAB-Based Resource Allocation for Efficient Bandwidth Utilization in Industrial IoT Networks by Dongyeong Seo, Kidong Nam, Kwansoo Jung

“…This approach improves the performance of industrial networks while maintaining compatibility with existing industrial network systems, supporting reliability and real-time processing. …”
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Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques by Stephanie Ness, Vishwanath Eswarakrishnan, Harish Sridharan, Varun Shinde, Naga Venkata Prasad Janapareddy, Vineet Dhanawat

“…By comparing different algorithms, this research contributes to advancing the application of machine learning in network security, offering guidance on model selection and optimization for improved detection of cyber threats.…”
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Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques by Daniel Amigo, David Sánchez Pedroche, Jesús García, José Manuel Molina, Jekaterina Trofimova, Emmanuel Voet, Benoît Van Bogaert

“…We introduce four key improvements: (1) a novel segmentation algorithm for more precise flight phase identification, (2) an improved invalid height detection process using LOWESS and sliding window analysis, (3) a protection mechanism against simultaneous measurements at the Kalman filter level, and (4) an optimized approach for smooth overshoot correction during segment transitions. …”
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An Adaptive Weight Physics-Informed Neural Network for Vortex-Induced Vibration Problems by Ping Zhu, Zhonglin Liu, Ziqing Xu, Junxue Lv

“…In this study, a VIV dataset of a cylindrical body with different degrees of freedom is used to compare the performance of the PINN and three PINN optimization algorithms. The findings suggest that, compared to a standard PINN, the AW-PINN lowers the mean squared error (MSE) on the test set by 50%, significantly improving the prediction accuracy. …”
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Toward a unified gait freeze index: a standardized benchmark for clinical and regulatory evaluations by Alessandro Schaer, Henrik Maurenbrecher, Carlo Mangiante, Roman Sobkuliak, Kathrin Müsch, Paula Sanchez Lopez, Eduardo Martin Moraud, Eduardo Martin Moraud, Olgac Ergeneman, George Chatzipirpiridis

“…Our method demonstrates improved performance compared to existing approaches while effectively mitigating the risk of divergent outcomes, which could otherwise lead to unforeseen and potentially hazardous consequences in real-world applications. …”
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Quantum circuit unoptimization by Yusei Mori, Hideaki Hakoshima, Kyohei Sudo, Toshio Mori, Kosuke Mitarai, Keisuke Fujii

“…In this paper, we define and construct a quantum algorithmic primitive called quantum circuit unoptimization, which makes a given quantum circuit complex by introducing some redundancies while preserving circuit equivalence, i.e., the inverse operation of circuit optimization. …”
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DynBlock: dynamic data encryption with Toffoli gate for IoT by Mubasher Haq, Ijaz Ali Shoukat, Alamgir Naushad, Mohsin Raza Jafri, Moid Sandhu, Abd Ullah Khan, Hyundong Shin

“…It is found that DynBlock significantly improves energy efficiency and throughput compared to its predecessors. …”
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Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography by Barbara Stefaniak, Tomasz Rymarczyk, Dariusz Wójcik, Marta Cholewa-Wiktor, Tomasz Cieplak, Zbigniew Orzeł, Janusz Gudowski, Ewa Golec, Michał Oleszek, Marcin Kowalski

“…Special attention is given to minimizing energy consumption during electromagnetic measurements and data processing, significantly improving the system’s overall performance. Research studies confirm the device’s high energy efficiency while maintaining the accuracy of the classification of lung disease using the LightGBM algorithm. …”
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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…The integration of these advanced algorithms accurately identified defects and categorized them, thus optimizing manufacturing processes. …”
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Explainable AI-Based Ensemble Clustering for Load Profiling and Demand Response by Elissaios Sarmas, Afroditi Fragkiadaki, Vangelis Marinakis

“…Notably, while ensemble clustering often ranked among the top performers, it did not consistently surpass all individual algorithms, indicating its potential for further optimization. …”
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Adaptive robust self‐scheduling for a wind‐based GenCo equipped with power‐to‐gas system and gas turbine to participate in electricity and natural gas markets by Mojtaba Fereydani, Mohammad Amin Latify

“…A column & constraint generation (C&CG) algorithm is used to solve the model. Numerical results demonstrate the model’s effectiveness in various case studies, showing that the GenCo can manage wind uncertainties, benefit from arbitrage opportunities in electricity and gas markets, and improve economic outcomes. …”
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Research on intelligent energy management strategies for connected range-extended electric vehicles based on multi-source information by Xuewen Zhai, Hanwu Liu, Wencai Sun, Zihang Su

“…Abstract Reliance solely on vehicle-specific information, while neglecting multi-source information such as traffic flow and traffic light status, results in difficulties in optimizing energy allocation based on complex road conditions. …”
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Power-Yeoh: A Yeoh-Type Hyperelastic Model with Invariant I₂ for Rubber-like Materials by Subraya Krishna Bhat, Keerthan A.

“…Also, the interesting phenomenon of thin balloon expansion is investigated by applying the model to relevant experimental data on elastomeric balloons available in the literature. A genetic algorithm-based least squares optimization routine is carried out to determine the material constants while applying the reported experimental data. …”
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