Investigation on the Role of Artificial Intelligence in Measurement System by P. A. Rezvy, Venkata Lakshmi Narayana Komanapalli

“…Soft computation using artificial neural networks and deep learning for linearization, compensation and error reduction, machine learning for estimation levaraging different algorithms like levenberg marquardt, scaled conjugate gradient, bayesian regularization, are assessed for training, testing and validation in real time and simulation. …”
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Formal Verification of Three-Valued Digital Waveforms by Nina Yu. Kutsak, Vladislav V. Podymov

“…The main results are mathematical notions, propositions, and algorithms which allow to formalize and solve a formal verification problem for considered waveforms, including: definitions for signals and waveforms which the mentioned typical digital signal features; a temporal logic suitable for formalization of waveform correctness properties, and a related verification problem statement; a solution technique for the verification problem, which is based on reduction to signal transfromation and analysis; a corresponding verification algorithm together with its correctness proof and “reasonable” complexity bounds.…”
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Smart Agile Prioritization and Clustering: An AI-Driven Approach for Requirements Prioritization by Aya M. Radwan, Manal A. Abdel-Fattah, Wael Mohamed

“…Various machine learning algorithms are tested, with KNN and Random Forest demonstrating the highest accuracy and lowest Mean Squared Error (MSE), outperforming traditional prioritization techniques. …”
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AstroM3: A Self-supervised Multimodal Model for Astronomy by M. Rizhko, J. S. Bloom

“…One surprising highlight is the “rediscovery” of Mira subtypes and two rotational variable subclasses using manifold learning and dimensionality reduction algorithms. To our knowledge this is the first construction of an n  > 2 mode model in astronomy. …”
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A Rapid Intelligent Screening of a Three-Band Index for Estimating Soil Copper Content by Shiyao Liu, Shichao Cui, Rengui Wang, Minming Han, Jingtao Kou

“…Moreover, integrating first-order derivative spectroscopy with CARS makes it possible to precisely identify key spectral bands and outperforms the dimensionality-reduction capabilities compared with the integration of STE. …”
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Multi-objective autonomous eco-driving strategy: A pathway to future green mobility by He Tong, Liang Chu, Zheng Chen, Yonggang Liu, Yuanjian Zhang, Jincheng Hu

“…With the wide popularity of electric vehicles in the market and advancements in autonomous driving technology, intelligent electric vehicles (iEVs) equipped with comprehensive eco-driving capabilities are expected to play a pivotal role in energy conservation and emission reduction of future mobility. This paper proposes an intelligent eco-driving strategy (IEDS) to address the safety and eco-driving concerns with the parallel hybrid electric vehicle (PHEV). …”
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SP-Pillars: An Efficient LiDAR 3D Objects Detection Framework With Multi-Scale Feature Perception and Optimization by Tingshuai Chen, Ye Yuan, Bingyang Yin, Yuanhong Liao

“…To address this challenge, this paper proposes a 3D object detection algorithm SP-Pillars that can effectively learn point cloud features. …”
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Real-Time Gas Path Fault Diagnosis for Aeroengines Based on Enhanced State-Space Modeling and State Tracking by Siyan Cao, Hongfu Zuo, Xincan Zhao, Chunyi Xia

“…The experimental results demonstrate a 0.714–2.953% RMSE in fault diagnosis performance, a 3.619% accuracy enhancement over traditional sliding mode observer algorithms, and 2.11 s reduction in settling time, eliminating noise accumulation. …”
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Optimising Connectivity and Energy: The Future of LoRaWAN Routing Protocols for Mobile IoT Applications by Izzah N. Buang, K. Zen, Syahrul N. Junaini

“…These approaches have demonstrated improvements in packet delivery ratios (PDRs), latency reduction, and energy efficiency within mobile IoT contexts. …”
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An adaptive continuous threshold wavelet denoising method for LiDAR echo signal by Dezhi Zheng, Tianchi Qu, Chun Hu, Shijia Lu, Zhongxiang Li, Guanyu Yang, Xiaojun Yang

“…Simulation results show that the proposed algorithm has excellent performance in improving SNR and reducing root mean square error (RMSE) compared with other algorithms. …”
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Description of route dependencies for computer-based railway signalling systems by Michał Grzybowski, Jakub Młyńczak, Lucyna Sokołowska

“…In addition, during research algorithms for automatic verification of conflicting route exclusion correctness have been designed, which allows for reduction of effort required for verification of conflicting route exclusion function. …”
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Application of edge computing technology in smart grid data security by Zhuo Cheng, Jiangxin Li, Jianjun Zhang, Chen Wang, Hui Wang, Juyin Wu

“…The experimental results indicate that: The total running time required for executing proxy authorization and verification, proxy key generation, signature and decryption algorithms in this scheme is 5.617 ms, with a ciphertext length of 80 Bytes. …”
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Research on the Dynamic Modeling of Rigid–Flexible Composite Spacecraft Under Fixed Constraints Based on the ANCF by Jiaqi Wu, Guohua Kang, Junfeng Wu, Chuanxiao Xu, Jiayi Zhou, Xinyong Tao, Yinmiao Hua

“…MATLAB simulations demonstrate that the proposed dynamic model alleviates the dimensionality disaster caused by conventional algorithms, significantly reducing computation time. …”
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Optimizing Skin Quality via AI-Enhanced Physical Activity by Niki Tertipi, Eleni Sfyri, Vasiliki Sofia Grech, Vasiliki Kefala, Efstathios Rallis

“…Regular exercise has well-documented benefits for skin physiology, including enhanced microcirculation, improved collagen synthesis, oxidative stress reduction, and modulation of inflammatory pathways. …”
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On the role of diagnosis of prostate diseases at the outpatient appointment of a therapist by A. L. Kebina, A. S. Sycheva, A. L. Vertkin, G. Yu. Knorring

“…Identification of symptoms suspicious of malignant neoplasms using algorithmic approaches and subsequent consultation with the patient by a specialist urologist or oncologist should improve treatment outcomes.…”
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A reversible and robust hybrid image steganography framework using radon transform and integer lifting wavelet transform by B. M. El-den, Walid Raslan

“…High Normalized Correlation Coefficient (NCC) values close to 1 further confirm the algorithm’s reversibility and integrity, even under common attacks such as Gaussian Noise, Poisson Noise, Blurring, and Cropping. …”
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Robotic Tack Welding Path and Trajectory Optimization Using an LF-IWOA by Bingqi Jia, Haihong Pan, Lei Zhang, Yifan Yang, Huaxin Chen, Lin Chen

“…For Workpiece 1, the algorithm reduces the welding path by up to 25.53% compared to the genetic algorithm, with an average reduction of 14.82% across benchmarks. …”
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Spot Image Segmentation of Lifting Container Vibration Based on Improved Threshold Method and Mathematical Morphology by Tian-Bing Ma, Qiang Wu, Fei Du, Wei-Kang Hu, Yong-Jing Ding

“…We used MCE to evaluate the segmentation effect of threshold segmentation and verified the improved algorithm’s accuracy by detecting the pixel centroid of laser spots. …”
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Improving Localization in Wireless Sensor Networks for the Internet of Things Using Data Replication-Based Deep Neural Networks by Jehan Esheh, Sofiene Affes

“…The proposed DAS replicates the estimated positions of unknown nodes generated by the Dv-hop algorithm and introduces Gaussian noise to these replicated positions, creating multiple modified datasets. …”
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Classification of Lung Nodule Using Hybridized Deep Feature Technique by Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham

“…The machine learning algorithms such as SVM and Logistic Regression have been used to classify the nodules based on the features. …”
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