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

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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A bio-inspired optical imaging method for robotic perception in turbid water

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science China Technological sciences 2025年第1期 79-81页

作者： Xudong SUN Yafeng LI Peng LIN Xiaodi SHANG Xianping FU school of Information science and Technology Dalian Maritime University College of computer science and Technology Qingdao University

In the realm of underwater robotics, optical imaging plays a pivotal role in many scientific researches. Due to the effects of absorption and scattering,images captured in turbid water are severely degraded. Therefore, enhancing the quality of underwater optical images stands paramount in ensuring the continued advancement and efficacy of underwater robots across its multifarious applications.

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A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

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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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Multi-receptive field interaction network for shape from polarization

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science China(Information sciences) 2025年第1期 394-395页

作者： Yini PENG Rui LIU Zhiyuan ZHANG Zhongyuan WANG Jiayi MA Xin TIAN Electronic Information school Wuhan University computer science school Wuhan University Wuhan Institute of Quantum Technology

Shape from polarization (SfP) method can use the polarization information in reflected light to estimate the surface normal of the target,which can further reconstruct the shape of the *** a simple image capture process,it can use low-cost equipment to meet a high precision imaging requirement,which can be used in remote scenes and other applications.

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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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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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Ru doping triggering reconstruction of cobalt phosphide for coupling glycerol electrooxidation with seawater electrolysis

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Journal of Energy Chemistry 2025年第1期100卷 317-326页

作者： Binglu Deng Jie Shen Jinxing Lu Chuqiang Huang Zhuoyuan Chen Feng Peng Yunpeng Liu school of Materials science and Hydrogen Energy Foshan University school of Chemistry and Chemical Engineering Guangzhou University Guangdong Key Laboratory for Hydrogen Energy Technologies

Seawater electrolysis is a promising approach for sustainable energy without relying on precious ***,the large-scale seawater electrolysis is hindered by low catalytic efficiency and severe anode corrosion caused by the harmful *** contrast to the oxygen evolution reaction （OER）and chlorin ion oxidation reaction （ClOR）,glycerol oxidation reaction （GOR） is more thermodynamically and kinetically favorable ***,a Ru doping cobalt phosphide （Ru-CoP2） is proposed as a robust bifunctional electrocatalyst for seawater electrolysis and GOR,for the concurrent productions of hydrogen and value-added *** in situ and ex situ characterization analyses demonstrated that Ru doping featured in the dynamic reconstruction process from Ru-CoP2to Ru-CoOOH,accounting for the superior GOR *** coupling GOR with hydrogen evolution was realized by employing Ru-CoP2as both anode and cathode,requiring only a low voltage of 1.43 V at 100 mA cm-2,which was 250 m V lower than that in alkaline *** work guides the design of bifunctional electrocatalysts for energy-efficient seawater electrolysis coupled with biomass resource upcycling.

关键词： Glycerol electrooxidation Hydrogen evolution Ru doping Cobalt phosphide Bifunctional electrocatalysts

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SensFL:Privacy-Preserving Vertical Federated Learning with Sensitive Regularization

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computer Modeling in Engineering & sciences 2025年第1期142卷 385-404页

作者： Chongzhen Zhang Zhichen Liu Xiangrui Xu Fuqiang Hu Jiao Dai Baigen Cai Wei Wang school of Automation and Intelligence Beijing Jiaotong UniversityBeijing100044China Shuohuang Railway Development Co. Ltd.National Energy GroupCangzhou062350China Beijing Key Laboratory of Security and Privacy in Intelligent Transportation School of Computer Science and TechnologyBeijing Jiaotong UniversityBeijing100044China

In the realm of Intelligent Railway Transportation Systems,effective multi-party collaboration is crucial due to concerns over privacy and data *** Federated Learning(VFL)has emerged as a promising approach to facilitate such collaboration,allowing diverse entities to collectively enhance machine learning models without the need to share sensitive training ***,existing works have highlighted VFL’s susceptibility to privacy inference attacks,where an honest but curious server could potentially reconstruct a client’s raw data from embeddings uploaded by the *** vulnerability poses a significant threat to VFL-based intelligent railway transportation *** this paper,we introduce SensFL,a novel privacy-enhancing method to against privacy inference attacks in ***,SensFL integrates regularization of the sensitivity of embeddings to the original data into the model training process,effectively limiting the information contained in shared *** reducing the sensitivity of embeddings to the original data,SensFL can effectively resist reverse privacy attacks and prevent the reconstruction of the original data from the *** experiments were conducted on four distinct datasets and three different models to demonstrate the efficacy of *** results show that SensFL can effectively mitigate privacy inference attacks while maintaining the accuracy of the primary learning *** results underscore SensFL’s potential to advance privacy protection technologies within VFL-based intelligent railway systems,addressing critical security concerns in collaborative learning environments.

关键词： Vertical federated learning privacy defenses

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CableSAM:an efficient automatic segmentation method for aircraft cabin cables

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Optoelectronics Letters 2025年第3期 183-187页

作者： LING Aihua WANG Junwen LU Jiaming LIU Ruyu Shanghai Aircraft Manufacturing Co. Ltd. school of computer science and Engineering Tianjin University of Technology school of Information science and Technology Hangzhou Normal University

Cabin cables,as critical components of an aircraft's electrical system,significantly impact the operational efficiency and safety of the *** existing cable segmentation methods in civil aviation cabins are limited,especially in automation,heavily dependent on large amounts of data and resources,lacking the flexibility to adapt to different *** address these challenges,this paper introduces a novel image segmentation model,CableSAM,specifically designed for automated segmentation of cabin *** improves segmentation efficiency and accuracy using knowledge distillation and employs a context ensemble *** accurately segments cables in various scenarios with minimal input *** experiments on three cable datasets demonstrate that CableSAM surpasses other advanced cable segmentation methods in performance.

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Transforming Education with Photogrammetry:Creating Realistic 3D Objects for Augmented Reality Applications

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computer Modeling in Engineering & sciences 2025年第1期142卷 185-208页

作者： Kaviyaraj Ravichandran Uma Mohan Department of Computational Intelligence School of ComputingSRM Institute of Science and TechnologyKattankulathur603203India

Augmented reality(AR)is an emerging dynamic technology that effectively supports education across different *** increased use of mobile devices has an even greater *** the demand for AR applications in education continues to increase,educators actively seek innovative and immersive methods to engage students in ***,exploring these possibilities also entails identifying and overcoming existing barriers to optimal educational ***,this surge in demand has prompted the identification of specific barriers,one of which is three-dimensional(3D)*** 3D objects for augmented reality education applications can be challenging and time-consuming for the *** address this,we have developed a pipeline that creates realistic 3D objects from the two-dimensional(2D)*** for augmented and virtual reality can then utilize these created 3D *** evaluated the proposed pipeline based on the usability of the 3D object and performance ***,with 117 respondents,the co-creation team was surveyed with openended questions to evaluate the precision of the 3D object created by the proposed photogrammetry *** analyzed the survey data using descriptive-analytical methods and found that the proposed pipeline produces 3D models that are positively accurate when compared to real-world objects,with an average mean score above *** study adds new knowledge in creating 3D objects for augmented reality applications by using the photogrammetry technique;finally,it discusses potential problems and future research directions for 3D objects in the education sector.

关键词： Augmented reality education immersive learning 3D object creation photogrammetry and StructureFromMotion

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