Target Recognition Method Based on Graph Structure Perception of Invariant Features for SAR Images by Jingyi CAO, Yang ZHANG, Ya’nan YOU, Yamin WANG, Feng YANG, Weijia REN, Jun LIU

“…The t-Distributed Stochastic Neighbor Embedding (t-SNE) method is used to qualitatively evaluate the algorithm’s classification ability, while metrics like accuracy, recall, and F1 score are used to quantitatively analyze key units and overall network performance. …”
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Comparison of Deep Learning-Based Auto-Segmentation Results on Daily Kilovoltage, Megavoltage, and Cone Beam CT Images in Image-Guided Radiotherapy by Zhixing Wang PhD, Chengyu Shi PhD, Carson Wong BS, Seyi M Oderinde PhD, William T Watkins PhD, Kun Qing PhD, Bo Liu PhD, Terence M Williams MD, PhD, An Liu PhD, Chunhui Han PhD

“…Introduction This study aims to evaluate auto-segmentation results using deep learning-based auto-segmentation models on different online CT imaging modalities in image-guided radiotherapy. …”
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Multi-objective optimization of sustainable cement-zeolite improved sand based on life cycle assessment and artificial intelligence [version 1; peer review: 1 approved, 2 approved... by Hossein MolaAbasi, Satinder Kaur Brar, Amin Tanhadoust, Sepideh Nasrollahpour, Omolbanin Ataee, Moncef L. Nehdi

“…This study proposes a multi-objective optimization approach using back-propagation neural network (BPNN) to predict the mechanical strength, along with an adaptive geometry estimation-based multi-objective evolutionary algorithm (AGE-MOEA) to identify the best parameters for cement-zeolite-improved sand, filling a long-lasting research gap. …”
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Reinforcement Learning-Based Control for Robotic Flexible Element Disassembly by Benjamín Tapia Sal Paz, Gorka Sorrosal, Aitziber Mancisidor, Carlos Calleja, Itziar Cabanes

“…The RL-based approach is evaluated in a simulation using soft actor–critic (SAC), deep deterministic policy gradient (DDPG), and proximal policy optimization (PPO) algorithms, benchmarking their effectiveness in dynamic environments. …”
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Optimized Hierarchical Sliding Mode Control for the Swing-Up and Stabilization of a Rotary Inverted Pendulum by Duc-Binh Pham, Quy-Thinh Dao, Thi-Van-Anh Nguyen

“…The integration of the PSO algorithm enhances the controller’s adaptability and robustness, emphasizing the benefits of combining optimization algorithms with controller parameter tuning for underactuated systems like the RIP.…”
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Spectral Fingerprinting of Tencha Processing: Optimising the Detection of Total Free Amino Acid Content in Processing Lines by Hyperspectral Analysis by Qinghai He, Yihang Guo, Xiaoli Li, Yong He, Zhi Lin, Hui Zeng

“…This study employs VNIR-HSI combined with machine learning algorithms to develop a model for visualizing the total free amino acid content in Tencha samples that have undergone different processing steps on the production line. …”
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Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach by Reshma Ahmed Swarna, Muhammad Minoar Hossain, Mst. Rokeya Khatun, Mohammad Motiur Rahman, Arslan Munir

“…Enhanced algorithms and analysis techniques are needed for more accurate assessments. …”
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Studies and Rejection of Intercrystal Crosstalk on FPGA in a High-Energy Photon-Counting System by Jiahao Chang, Huaxia Zhang, Shibo Jiang, Zhifang Wu, Shuo Xu

“…The suggested method has been proven effective in producing higher-quality images and demonstrates good adaptability by adapting the detector window width according to different system count rates.…”
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Using S-Curve Transforms and Gamma Correction for MR Images Contrast Enhancement by Manar Al-Abaji, Zohair Al-Ameen

“…Moreover, it was compared with four different CE approaches and evaluated using three measures. …”
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High-precision deformation monitoring and intelligent early warning for wellbore based on BDS/GNSS. by Jiang Li, Lei Dai, Keke Xu, Xinyu Mei, Yifu Liu, Jianlin Shi, Hebing Zhang

“…A quantitative analysis was conducted on the performance of various combinations of BDS/GNSS in wellbore deformation monitoring, and the effects of different baseline lengths on the monitoring results were evaluated. …”
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Fault Diagnosis of Rolling-Element Bearing Using Multiscale Pattern Gradient Spectrum Entropy Coupled with Laplacian Score by Xiaoan Yan, Ying Liu, Peng Ding, Minping Jia

“…Results confirm the availability of our proposed algorithm in feature extraction and show that our method can recognize effectively different bearing fault categories and severities. …”
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Automated Quality Control of Cleaning Processes in Automotive Components Using Blob Analysis by Simone Mari, Giovanni Bucci, Fabrizio Ciancetta, Edoardo Fiorucci, Andrea Fioravanti

“…The system acquires high-resolution monochrome images under various lighting configurations, including natural light and infrared (IR) at 850 nm and 940 nm, with different angles of incidence. Four blob detection algorithms—adaptive thresholding, Laplacian of Gaussian (LoG), Difference of Gaussians (DoG), and Determinant of Hessian (DoH)—were implemented and evaluated based on their ability to detect surface impurities. …”
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Inhomogeneous Illumination Image Enhancement Under Extremely Low Visibility Condition by Libang Chen, Jinyan Lin, Qihang Bian, Yikun Liu, Jianying Zhou

“…We introduce in this paper a novel method that adaptively filters background illumination based on Structural Differential and Integral Filtering (SDIF) to enhance only the vital signal information. …”
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WINTER HARDINESS OF BREAD WHEAT FROM THE VIR COLLECTION IN ENVIRONMENTS OF THE NORTHWESTERN AND CENTRAL BLACK SOIL REGIONS OF RUSSIA by N. S. Lysenko, V. F. Loseva, O. P. Mitrofanova

“…By using the cluster analysis (k-means algorithm), the target sub-collec­tion structure has been revealed. …”
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TKEO-Enhanced Machine Learning for Classification of Bearing Faults in Predictive Maintenance by Xuanbai Yu, Olivier Caspary

“…The effectiveness of TKEO was compared against conventional methods, using the Case Western Reserve University (CWRU) dataset, with vibration data collected from bearings operating under different load conditions. Different data segmentation lengths (2400 and 12,000 samples) were evaluated to assess the impact of segment size on classification accuracy. …”
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Prevalence of advanced liver fibrosis in the general population of the Paris region according to FIB-4 score and liver risk score by Henri Tran, Stefano Caruso, Anne-Laure Mazialivoua, Cecile Fargeat, Odile Rousselet, Adrien Ko, Vincent Leroy, Patrick Ingiliz

“…An adapted new pragmatic screening algorithm using LRS should be considered.…”
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Modeling and Simulation of Energy-Regenerative Active Suspension Based on BP Neural Network PID Control by Jiang Liu, Xinjun Li, Xilong Zhang, Xiufeng Chen

“…Meanwhile, the BP-PID algorithm also enables the suspension system’s self-adaptability and stability characteristics on its energy recovery capability.…”
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Predicting Missing Links Based on Power-Law Distribution and Information Transmission Efficiency by Yi Wang, Jun Ma

“…The proposed method does not require manual parameter tuning, making it more efficient and adaptable to different networks. Through experiments on multiple real-world networks, the algorithm demonstrates high prediction accuracy and achieves impressive results when evaluated using standard metrics. …”
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Personalised Affective Classification Through Enhanced EEG Signal Analysis by Joseph Barrowclough, Nonso Nnamoko, Ioannis Korkontzelos

“…This overlooks individual differences and may not accurately capture the unique emotional patterns of each person.Methods This study explored the performance of six machine learning algorithms in classifying a benchmark EEG dataset (collected with a MUSE device) for affective research. …”
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Development and Validation of a Radiomics Nomogram Based on Magnetic Resonance Imaging and Clinicoradiological Factors to Predict HCC TACE Refractoriness by Dong Y, Hu J, Meng X, Yang B, Peng C, Zhao W

“…Relevant indices of TACE refractoriness were selected. ML algorithms, including a support vector machine, random forest, logistic regression and adaptive boosting, were used to construct the radiomics, clinical prediction, and combined models. …”
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