2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration by Ke-Yu Yao, Derek Ka-Hei Lai, Hyo-Jung Lim, Bryan Pak-Hei So, Andy Chi-Ho Chan, Patrick Yiu-Man Yip, Duo Wai-Chi Wong, Bingyang Dai, Xin Zhao, Siu Hong Dexter Wong, James Chung-Wai Cheung

“…Intelligent piezoresistive health monitoring systems integrate advanced nanocomposite architectures with precise algorithmic analysis for real-time physiological assessment. …”
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Dynamically Adapted Mesh Construction for the Efficient Numerical Solution of a Singular Perturbed Reaction-diffusion-advection Equation by Dmitry V. Lukyanenko, Vladimir T. Volkov, Nikolay N. Nefedov

“…This  work develops  a theory  of the  asymptotic-numerical investigation of the  moving fronts  in reaction-diffusion-advection models.  By considering  the  numerical  solution  of the  singularly perturbed Burgers’s  equation  we discuss a method  of dynamically  adapted mesh  construction that is able to significantly  improve  the  numerical  solution  of this  type of equations.  …”
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Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…However, it remains to answer the question of the need to improve the efficiency of an already implemented network, and, therefore, to conduct research on methods to improve the efficiency of networks, including finer tuning of parameters and learning algorithms, as well as architecture.A well-known and obvious drawback of using LSTMs is their exactingness in terms of equipment and resources, both during training (the training process takes a significant amount of time) and during startup, in our case, it is supplemented by increased requirements for the training sample and casts doubt on the advisability of further study of LSTM networks when solving this task.Conclusion. …”
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Research Progress on Identification and Extraction Methods of Soil and Water Conservation Measures by TIAN Pei, REN Yiling, CHEN Yan

“…Extraction of point and linear engineering measures; the combination of deep learning algorithms such as multimodal learning and instance segmentation methods with object-oriented classification methods is applied to the identification and extraction of soil and water conservation plant measures to improve the classification and extraction accuracy of different soil and water conservation plant measures. …”
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Research on AIGC-Driven Personalized Mathematics Learning System by Wang Chenggang

“…By integrating generative AI models, adaptive learning algorithms, and real-time feedback mechanisms, the system seeks to enhance student engagement, improve learning outcomes, and foster a deeper understanding of mathematical concepts. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…The results highlight the system’s effectiveness in detecting security threats and improving navigation through adaptive recommendations. …”
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Identifying Data-Driven Clinical Subgroups for Cervical Cancer Prevention With Machine Learning: Population-Based, External, and Diagnostic Validation Study by Zhen Lu, Binhua Dong, Hongning Cai, Tian Tian, Junfeng Wang, Leiwen Fu, Bingyi Wang, Weijie Zhang, Shaomei Lin, Xunyuan Tuo, Juntao Wang, Tianjie Yang, Xinxin Huang, Zheng Zheng, Huifeng Xue, Shuxia Xu, Siyang Liu, Pengming Sun, Huachun Zou

“…Personalized, data-driven cervical cancer prevention (CCP) strategies tailored to phenotypic profiles may improve prevention and reduce disease burden. …”
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An Experimental Study of GPR Near-Field Problem in Depth Ranging of Buried Objects by Rex Yui Kei Cham, Wallace Wai Lok Lai

“…Then, the same antenna was used to estimate the cover depth by measuring the time of flight and velocity based on the two velocity algorithms. The results reveal that the ranging accuracy is highly in doubt in reactive near-field and Fresnel regions but is largely improved when the object locates in far-field region where GPR wave propagation becomes plane-type. …”
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Prediction of Myocardial Infarction Based on Non-ECG Sleep Data Combined With Domain Knowledge by Changyun Li, Yonghan Zhao, Qihui Mo, Zhibing Wang, Xi Xu

“…The experiments demonstrate that the model’s accuracy reaches its optimal level by combining the age rule, improving to 73.1%. …”
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Evaluation of Smart Building Integration into a Smart City by Applying Machine Learning Techniques by Mustafa Muthanna Najm Shahrabani, Rasa Apanaviciene

“…The conclusion of this study states that by utilising the developed machine learning model, owners and policymakers are capable of significantly improving the integration of smart buildings to build better, more sustainable, and resilient urban environments.…”
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A survey of sand-dust image visual enhancement techniques by SI Yazhong, ZHANG Xulong, YANG Fan, WANG Jianzong, CHENG Ning, XIAO Jing

“…The visual enhancement technology of sandstorm images aims to improve the visual perception clarity of the captured data by imaging equipment under sandstorm weather, assisting high-level vision algorithms to enhance the ability to obtain key features from the data. …”
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Clock factorized quantum Monte Carlo method for long-range interacting systems by Zhijie Fan, Chao Zhang, Youjin Deng

“…Next, we show how the clock factorized quantum Monte Carlo method can be flexibly implemented in various update strategies, like the Metropolis and worm-type algorithms. Finally, we demonstrate the high efficiency of the clock factorized quantum Monte Carlo algorithms using examples of three typical long-range interacting quantum systems, including the transverse field Ising model with long-range $z$-$z$ interaction, the extended Bose-Hubbard model with long-range density-density interactions, and the XXZ Heisenberg model with long-range spin interactions. …”
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Dynamic Optimization of Tunnel Construction Scheduling in a Reverse Construction Scenario by Jianying Wei, Yuming Liu, Xiaochun Lu, Rong Zhao, Gan Wang

“…The Mixed-Integer Programming (MIP) approach is used to build the mathematical model, solved with both exact algorithms and Genetic Algorithms (GA), and implemented in Python 3.12.7. …”
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Enhanced Position-Aided Beam Prediction Using Real-World Data and Enhanced-Convolutional Neural Networks by Ahmed Abd El Moaty Mohamed Gouda, Ehab K. I. Hamad, Aziza I. Hussein, M. Mourad Mabrook, A. A. Donkol

“…The proposed E-CNN model has been investigated across nine different scenarios from the DeepSense 6G dataset and compared against the conventional algorithms. …”
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Utilization of fine needle aspiration cytology at Kamuzu central hospital. by Shiraz Khan, George Liomba, Nora E Rosenberg, Christopher Stanley, Cocxilly Kampani, Bal Mukunda Dhungel, Mina C Hosseinipour

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PFRNet: A Small Object Detection Method Based on Parallel Feature Extraction and Attention Mechanism by Hai Lin, Ji Wang, Jingguo Li

“…In addition, PFRNet introduces the spatial pyramid pooling fusion with spatial attention (SPPFSPA) module, which integrates multi-scale features with an attention mechanism, enabling the model to better focus on areas of interest, thereby improving detection performance. …”
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A Large-Scale Inter-Comparison and Evaluation of Spatial Feature Engineering Strategies for Forest Aboveground Biomass Estimation Using Landsat Satellite Imagery by John B. Kilbride, Robert E. Kennedy

“…We contextualize this improvement model performance by comparing to AGB models developed with multi-temporal features derived from the LandTrendr and Continuous Change Detection and Classification algorithms. …”
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Enhancing Daylight and Energy Efficiency in Hot Climate Regions with a Perforated Shading System Using a Hybrid Approach Considering Different Case Studies by Basma Gaber, Changhong Zhan, Xueying Han, Mohamed Omar, Guanghao Li

“…A hybrid approach integrating parametric modeling, machine learning, multi-criteria decision-making (MCDM), and genetic algorithm (GA) is used to optimize the design incorporating architects’ preferences. …”
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From Classic to Cutting-Edge: A Near-Perfect Global Thresholding Approach with Machine Learning by Nicolae Tarbă, Costin-Anton Boiangiu, Mihai-Lucian Voncilă

“…We apply our approach to a popular computer vision problem, document image binarization, and compare popular metrics with the best possible values achievable through global thresholding and with the values obtained through the algorithms we used to train our model. Our results show a significant improvement over these classical global thresholding algorithms, achieving near-perfect scores on all the computed metrics. …”
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Advancing Sika deer detection and distance estimation through comprehensive camera calibration and distortion analysis by Sandhya Sharma, Stefan Baar, Bishnu P. Gautam, Shinya Watanabe, Satoshi Kondo, Kazuhiko Sato

“…The calculated coefficients successfully corrected these distortions, improving image accuracy. The derived coefficients effectively corrected these distortions, improving image accuracy. …”
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