Implementation of Method of Minimizing the Side Lobe Level of Autocorrelation Functions of Signals With Nonlinear Frequency Modulation by O. O. Kostyria, A. A. Hryzo, I. A. Khizhnyak, A. V. Fedorov, A. A. Lukianchykov

“…In further research, it is planned to develop an algorithm for optimizing the time-frequency parameters of signals with nonlinear frequency modulation based on mathematical models of current and shifted time. …”
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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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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
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Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…Accurate early diagnosis and prediction of potential failures have the capability to greatly improve maintenance efficiency, minimize downtime, and optimize cost.…”
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A Camera-Embedded Self-Adaptable Finger With Multi-Modal Sensing Capabilities for Robotic Manipulation by Muhammad Usman Khalid, Hafiz Muizz Ahmed Sethi, Nirmal Kumar Ravikumar, Halar Haleem, Alessandro Seitone, Mattia Frascio, Perla Maiolino, Matteo Zoppi

“…Customized rigs integrated with a Universal Testing Machine (UTM) were used for sensor characterization, dataset acquisition, and slip detection parameter optimization. Furthermore, the system was validated through integration with an industrial gripper in an experimental sequence on different object types to mimic real-world manipulation, where both algorithms were integrated and deployed on Raspberry Pi 5 to achieve proprioceptive and exteroceptive sensing. …”
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Corporate Real Estate alignment by Monique Arkesteijn

“…The alternative design that adds most value to the organization, i.e. has the highest overall preference score, is the portfolio that optimally aligns real estate to corporate strategy. …”
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AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women by Li Ma, Li Ma, Ru Chen, Weigong Ge, Paul Rogers, Beverly Lyn-Cook, Huixiao Hong, Weida Tong, Ningning Wu, Wen Zou

“…In addition, BERTopic has the connection port for ChatGPT-4-Turbo or other large language models in its algorithm for automatic interpretation, while with LDA interpretation must be manually, and needs special procedures for data pre-processing and stop words exclusion. …”
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Synthesis of evasive maneuver control of unmanned aerial vehicle for terminal restrictions by N. Y. Polovinchuk, S. V. Ivanov, L. I. Kotelnitskaya

“…The work objective is to build an algorithm for solving the problem of synthesis of terminal optimal control of motion of center of mass of highspeed UAV that allows searching for the optimal control in function of the current coordinates of the object. …”
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Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…SGD, Adam, NAdam and RMSprop implemented in Keras were compared as optimizers to achieve faster convergence. Adam showed the best results in terms of accuracy, while the MSE loss function (mean square error) was used together with the optimizer. …”
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The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics by Leonel J. R. Nunes

“…Results: The results demonstrated that optimization algorithms reduced transportation costs and carbon emissions. …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…The approach addresses key limitations in UBEM while offering a robust tool for policymakers and urban planners to optimize energy consumption and reduce carbon emissions. …”
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Efficient Context-Preserving Encoding and Decoding of Compositional Structures Using Sparse Binary Representations by Roman Malits, Avi Mendelson

“…In addition, the proposed algorithms allow to optimize the amount of compute and memory needed to achieve the desired encoding/decoding performance.…”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…Bayesian optimization fine-tuned each model's hyperparameters to identify the optimal model-FS combination. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Eventually, the walrus optimization algorithm (WOA) is used for hyperparameter tuning to improve the parameters of the SSAE approach and achieve optimal performance. …”
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Coal mining equipment lifecycle management system architecture and key technology by Yihui PANG, Jinglong BI, Pengzhe YUAN, Baofu ZHAO, Ziwei DING

“…An optimization algorithm and software platform for comprehensive mining equipment selection were developed, and a method for constructing a series spectrum and coding system for coal mining equipment was proposed. …”
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A Novel Smart Molecular Fuzzy Decision Support System for Solid-State Battery Investments in Grid-Level Renewable Energy Storage by Gang Kou, Hasan Dincer, Serhat Yuksel, Edanur Ergun, Serkan Eti

“…For this purpose, a new decision-making model is developed that includes expert weighting with the entropy game, evaluation balancing with the Q-learning algorithm, calculation of criterion weights with the least squares optimization (LSO) and alternative ranking with the molecular ranking (MORAN) method. …”
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Reinforcement Q-Learning-Based Adaptive Encryption Model for Cyberthreat Mitigation in Wireless Sensor Networks by Sreeja Balachandran Nair Premakumari, Gopikrishnan Sundaram, Marco Rivera, Patrick Wheeler, Ricardo E. Pérez Guzmán

“…The framework integrates dynamic Q-learning for optimizing energy efficiency in low-threat conditions and double Q-learning for robust security adaptation in high-threat environments. …”
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The Current Development Status of Agricultural Machinery Chassis in Hilly and Mountainous Regions by Renkai Ding, Xiangyuan Qi, Xuwen Chen, Yixin Mei, Anze Li

“…In alignment with China’s “Dual Carbon” strategy and the unique operational requirements of hilly–mountainous areas (such as high gradients, uneven terrain, and small field sizes), this study proposes three key technological directions for the development of intelligent agricultural machinery chassis: (1) Multi-mode traveling mechanism design: Aimed at improving terrain traversability (ground clearance ≥400 mm, obstacle-crossing height ≥ 250 mm) and traction stability (slip ratio < 15%) across diverse landscapes. (2) Coordinated control algorithm optimization: Designed to ensure stable torque output (fluctuation rate < ±10%) and maintain gradient operation efficiency (e.g., less than 15% efficiency loss on 25° slopes) through power–drive synergy while also optimizing energy management strategies. (3) Intelligent perception system integration: Facilitating high-precision adaptive leveling (accuracy ± 0.5°, response time < 3 s) and enabling terrain-adaptive mechanism optimization to enhance platform stability and operational safety. …”
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Inherent Trade-Offs Between the Conflicting Aspects of Designing the Compact Global Navigation Satellite System (GNSS) Anti-Interference Array by Xiangjun Li, Xiaoyu Zhao, Xiaozhou Ye, Zukun Lu, Feixue Wang, Peiguo Liu

“…Building on these insights, we innovatively propose a multi-objective optimization framework based on the non-dominated sorting genetic algorithm-II (NSGA-II) model, integrating antenna electromagnetic characteristics and signal processing constraints. …”
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Local power flow control by L. M. Chetochnikova, N. I. Smolentsev, N. V. Tomskich, D. A. Gimgina, D. A. Lavrentieva

“…The  considered power management algorithm is a simple implementation of classical load balancing, and at the same time allows for optimal energy distribution within a given error. …”
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