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A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

computer Modeling in engineering & Sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing Chen Salman A.AlQahtani Hongrong Chen Bo Yang Siyu Lu Wenfeng Zheng Department of computer Science and engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea school of electrical and computer engineering Louisiana State UniversityBaton RougeLA 70803USA Department of computer engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia school of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation

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LoRa Sense:Sensing and Optimization of LoRa Link Behavior Using Path-Loss Models in Open-Cast Mines

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computer Modeling in engineering & Sciences 2025年第1期142卷 425-466页

作者： Bhanu Pratap Reddy Bhavanam Prashanth Ragam school of computer Science and engineering VIT-AP UniversityAmaravati52237India

The Internet of Things(IoT)has orchestrated various domains in numerous applications,contributing significantly to the growth of the smart world,even in regions with low literacy rates,boosting socio-economic *** study provides valuable insights into optimizing wireless communication,paving the way for a more connected and productive future in the mining *** IoT revolution is advancing across industries,but harsh geometric environments,including open-pit mines,pose unique challenges for reliable *** advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency(RF)protocols such as Bluetooth,Wi-Fi,GSM/GPRS,Narrow Band(NB)-IoT,SigFox,ZigBee,and Long Range Wireless Area Network(LoRaWAN).This study addresses the optimization of network implementations by comparing two leading free-spreading IoT-based RF protocols such as ZigBee and *** field tests are conducted in various opencast mines to investigate coverage potential and signal *** is tested in the Tadicherla open-cast coal mine in ***,LoRaWAN field tests are conducted at one of the associated cement companies(ACC)in the limestone mine in Bargarh,India,covering both Indoor-toOutdoor(I2O)and Outdoor-to-Outdoor(O2O)environments.A robust framework of path-loss models,referred to as Free space,Egli,Okumura-Hata,Cost231-Hata and Ericsson models,combined with key performance metrics,is employed to evaluate the patterns of signal *** field testing and careful data analysis revealed that the Egli model is the most consistent path-loss model for the ZigBee protocol in an I2O environment,with a coefficient of determination(R^(2))of 0.907,balanced error metrics such as Normalized Root Mean Square Error(NRMSE)of 0.030,Mean Square Error(MSE)of 4.950,Mean Absolute Percentage Error(MAPE)of 0.249 and Scatter Index(SI)of *** the O2O scenario,the Ericsson model

关键词： Internet of things long range wireless area network ZigBee mining environments path-loss models coefficient of determination mean square error

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Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.MUHAMMAD M.SARFRAZ Department of Humanities and Sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

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Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of electrical engineering and Automation Luoyang Institute of Science and Technology school of Mechanical engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

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Luminescence: a new perspective for investigating perovskite precursors

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Science China Materials 2025年第01期 312-313页

作者： Haofeng Zheng Shaocong Hou school of electrical engineering and Automation Wuhan University Wuhan University Shenzhen Research Institute

In the past two decades, perovskite materials have made significant progress in optoelectronic semiconductors, emerging as formidable candidates for the next generation of commercial solar cells, light-emitting diodes (LEDs), and *** the fundamental solution chemistry and photophysics in solution-processed perovskite devices is crucial for comprehending to achieve highly efficient optoelectronic devices.

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CaH2-promoted activity of Ni-carbonate interface for CO2 methanation

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Journal of Energy Chemistry 2025年第1期100卷 522-532页

作者： Jin-Peng Wang Guo-Cui Mao Hui-Lin Jiang Bao-Xia Dong Yun-Lei Teng school of Chemistry and Chemical engineering Yangzhou University

Transition metal-carbonate interfaces often act as active sites in heterogeneous catalytic *** interface between transition metal and metal carbonate exhibits a dynamic equilibrium during the CO2hydrogenation reaction,involving surface carbonate hydrogenation and ***,there have been few reports on engineering the activity of the interface between transition metal and alkaline earth metal carbonate for catalytic *** work demonstrated that the incorporation of CaH2in Ni/CaCO3enhances the CO2methanation activity of the *** CO2conversion for Ni/CaH2-CaCO3reached 68.5%at 400°C,which was much higher than that of the Ni/CaCO3（31.6%） and Ni/CaH2-CaO （42.4%） ***,the Ni/CaH2-CaCO3catalysts remained stable during the stability test for 24 h at 400°C and 8 *** research revealed that CaH2played a crucial role in promoting the activity of the Ni-carbonate interface for ***2could modify the electronic structure of Ni and tune the structural properties of CaCO3to generate medium basic sites （OH groups）,which are favorable for the activation of H2and ***-situ Fourier transform infrared spectroscopy （FTIR） analysis combined with density functional theory calculations demonstrated that CO2activation occurs at the hydroxyl group （OH） on the CaH2-modified Ni-carbonate surface,leading to the formation of CO3H****,our study has confirmed that CO2methanation over the Ni/CaH2-CaCO3catalysts proceeds via the formate pathway.

关键词： Metal hydride Ni catalysts Carbonate Metal-carbonate interface

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Buried interface bridging for inverted cesium-formamidinium triiodide perovskite solar cells with long operational stability

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Science China Chemistry 2025年第01期 163-173页

作者： Chenhui Zhang Chunjun Liang Fulin Sun Ting Zhu Xinghai Huang Yuzhu Guo Xinyu Guo Kunyang Ge Dan Li Fangtian You Zhiqun He Key Laboratory of Luminescence and optical Information Ministry of Education Institute of Optoelectronic TechnologyBeijing Jiaotong University Department of Physics School of Physical Science and Engineering Beijing Jiaotong University

In the field of perovskite solar cells(PSCs), the research on defects in the buried interface has been relatively limited due to its non-exposure; however, this interface significantly impacts the performance enhancement of inverted PSCs. This study employs phenylethylammonium chloride(PEACl) molecules as a buffer layer to modify the buried interface of p-i-n structured PSCs,aiming to enhance the uniformity of self-assembled monolayers(SAMs) and facilitate the uniform nucleation and growth of perovskite films on the substrate. Furthermore, the introduction of the PEACl buffer layer effectively passivates defects at the bottom of the perovskite layer and notably enhances the crystal quality of the perovskite film by mitigating residual stress,thereby reducing nonradiative recombination loss. Following these optimizations, the MA-free PSCs treated with PEACl achieve a power conversion efficiency(PCE) of 24.11%, with significant improvements in storage, thermal stability, and operational stability. Particularly noteworthy is the device's performance in an unencapsulated state, whereas after 1,500 hours of continuous light operation stability testing, it retains 97% of its original efficiency. This study not only enriches the systematic understanding of the characteristics of the buried interface in PSCs but also contributes significantly to advancing the commercial production of perovskite photovoltaic technology.

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Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

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Nano-Micro Letters 2025年第1期17卷 262-280页

作者： Dongxiao Li Hong Zhou Zhihao Ren Cheng Xu Chengkuo Lee Department of electrical and computer engineering National University of SingaporeSingapore 117583Singapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore

Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance ***,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning *** observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano *** characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 *** findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.

关键词： Plasmonic nanoantennas Light-matter interaction Surface-enhanced infrared absorption Overcoupled Biosensing

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Endoscopy-assisted lightweight diagnosis system based on transformers for colon polyp detection

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Optoelectronics Letters 2025年第1期21卷 57-64页

作者： FAN Weiming YU Jiahui JU Zhaojie school of Automation and electrical engineering Shenyang Ligong University Department of Biomedical engineering Zhejiang University school of Computing University of Portsmouth

The integration of endoscopy has significantly propelled the diagnosis and treatment of gastrointestinal diseases, with colonoscopy establishing itself as the primary method for early diagnosis and preventive care in colorectal cancer(CRC). Although deep learning holds promise in mitigating missed polyp rates, modern endoscopy examinations pose additional challenges, such as image blurring and atomizing. This study explores lightweight yet powerful attention mechanisms, introducing the spatial-channel transformer(SCT), an innovative approach that leverages spatial channel relationships for attention weight calculation. The method utilizes rotation operations for inter-dimensional dependencies, followed by residual transformation, encoding inter-channel and spatial information with minimal computational overhead. Extensive experiments on the CVC-Clinic DB polyp detection dataset, addressing endoscopy pitfalls, underscore the superiority of our SCT over other state-of-the-art methods. The proposed model maintains high performance, even in challenging scenarios.

关键词： Endoscopy

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Inspires effective alternatives to backpropagation:predictive coding helps understand and build learning

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Neural Regeneration Research 2025年第11期20卷 3215-3216页

作者： Zhenghua Xu Miao Yu Yuhang Song school of Health Sciences and Biomedical engineering Hebei University of TechnologyTianjinChina Department of computer Science University of OxfordOxfordUK

Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human *** enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.

关键词： assignment learning enable

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