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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

Prediction and optimization of flue pressure in sintering process based on SHAP

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 346-359页

作者： Mingyu Wang Jue Tang Mansheng Chu Quan Shi Zhen Zhang School of Metallurgy Northeastern UniversityShenyang 110819China Liaoning Low-Carbon Steelmaking technology Engineering Research Center Northeastern UniversityShenyang 110819China Engineering Research Center of Frontier Technologies for Low-Carbon Steelmaking(Ministry of Education) Shenyang 110819China

Sinter is the core raw material for blast *** pressure,which is an important state parameter,affects sinter *** this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment ***,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction *** effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment *** operating parameter combination was then *** flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.

关键词： sintering process flue pressure shapley additive explanation prediction optimization

Synergistic promotion strategy of “dual-site” and “dual-path” to enhance the C–C coupling between CO2 and HCHO driven by photoelectrocatalysis

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Journal of Energy Chemistry 2025年第1期100卷 39-49页

作者： Hongqiang Yang Jianfeng Zheng Guoyu Wang Yifei Gao Yatao Yang Jia Li Xiaojin Han Yan Cui Zhanggen Huang National Key Laboratory of High Efficiency and Low Carbon Utilization of Coal Institute of Coal Chemistry Chinese Academy of Science University of Chinese Academy of Science shenyang University of Chemical technology

Photoelectrocatalytic coupling CO2and volatile organic compounds （VOCs） is a promising green strategy for the synergistic conversion of the two carbon-containing resources to *** catalytic efficiency is always at the mercy of chemical inertness of CO2and the competitive hydrogen evolution of ***,a modified g-C3N4/ZnAl-LDH Z-scheme heterojunction catalyst with dual reaction site was rationally designed and precisely *** Faraday efficiency of ethanol reached 68.67%with a corresponding formation rate of 227.3μmol *** revealed by in-situ characterizations and density functional theory calculations,CO2and HCHO were absorbed at Zn site and N site,***,*CO generated from CO2and HCHO was converted to*CH3O and*CHO on the dual-active-site *** detailed reaction mechanism experiments indicated that C–C coupling only occurred between*CO and*CH3O in electrocatalysis *** from the“*CO+*CH3O”path,another“*CO+*CHO”coupling path was also detected in photoelectrocatalytic *** selectivity of ethanol was significantly enhanced due to the synthesis of dual-site catalyst and the dual-path coupling path between CO2and HCHO simultaneously driven by light and electricity.

关键词： Photoelectrocatalysis Z-scheme C–C coupling Ethanol

Dynamic evolution of Co species and morphological reconstruction on Co-N-C during the nitrate reduction reaction in neutral solution

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Nano Research 2025年第1期18卷 164-172页

作者： Yuanlin Fu Xiaoting Yang Ya Yu Kang Zhou Xiaoyang Ye Aoxiang Zhang Xiaojiao Hou Bingbing Chen Fuqiang Fan Yuhang Li Yu Fu Department of Chemistry College of SciencesNortheastern UniversityShenyang 110819China Department of Physical Education Shen Yang Institute of Science and TechnologyShenyang 110167China Sungrow Power Supply Co. Ltd.Hefei 230088China

The electrochemical nitrate reduction reaction(eNO_(3)^(-)RR)is considered an effective approach for converting nitrate-containing wastewater to *** adsorption and activation of NO_(3)^(-)is the critical step for many materials and the high energy barrier inhibits the continuation of the reduction *** Co nanoparticles encapsulated in the carbon layer we prepared spontaneously react with NO_(3)^(-)and the resulting Co^(2+)is then reduced by electroreduction to Co^(0),which circulates *** resulted in overcoming the energy input required for NO_(3)^(-)adsorption and conversion,thereby increasing the catalytic *** the same time,the morphology of the catalyst reconstructed from a dodecahedron to an interwoven nanosheet structure and the increased surface area also gives it better *** obtained Co(OH)_(2)@Co-N-C has an excellent eNO_(3)^(-)RR of 2774.7μg·h^(-1)·cm^(-2)with a Faraday efficiency of 81.4%in neutral *** the same time,the material-modified electrode can run stably for more than 100 *** work provides a new idea for the design of Co-based catalysts for eNO_(3)^(-)RR.

关键词： electrochemical nitrate reduction reaction Co-based catalyst dynamic evolution of Co species morphological reconstruction

Overview of in-situ oxygen production technologies for lunar resources

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 233-255页

作者： Youpeng Xu Sheng Pang Liangwei Cong Guoyu Qian Dong Wang Laishi Li Yusheng Wu Zhi Wang College of Materials Science and Engineering Shenyang University of TechnologyShenyang 110870China CAS Key Laboratory of Green Process and Engineering National Engineering Research Center for Green Recycling of Strategic Metal ResourcesInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China

The rich resources and unique environment of the Moon make it an ideal location for human expansion and the utilization of extraterrestrial ***,crucial for supporting human life on the Moon,can be extracted from lunar regolith,which is highly rich in oxygen and contains polymetallic *** oxygen and metal extraction can be achieved using existing metallurgical ***,the ample reserves of water ice on the Moon offer another means for oxygen *** paper offers a detailed overview of the leading technologies for achieving oxygen production on the Moon,drawing from an analysis of lunar resources and environmental *** delves into the principles,processes,advantages,and drawbacks of water-ice electrolysis,two-step oxygen production from lunar regolith,and one-step oxygen production from lunar *** two-step methods involve hydrogen reduction,carbothermal reduction,and hydrometallurgy,while the one-step methods encompass fluorination/chlorination,high-temperature decomposition,molten salt electrolysis,and molten regolith electrolysis(MOE).Following a thorough comparison of raw materials,equipment,technology,and economic viability,MOE is identified as the most promising approach for future in-situ oxygen production on the *** the corrosion characteristics of molten lunar regolith at high temperatures,along with the Moon's low-gravity environment,the development of inexpensive and stable inert anodes and electrolysis devices that can easily collect oxygen is critical for promoting MOE technology on the *** review significantly contributes to our understanding of in-situ oxygen production technologies on the Moon and supports upcoming lunar exploration initiatives.

关键词： lunar resources in-situ oxygen production space metallurgy molten lunar regolith electrolysis

Assessing the corrosion protection property of coatings loaded with corrosion inhibitors using the real-time atmospheric corrosion monitoring technique

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 119-126页

作者： Xiaoxue Wang Lulu Jin Jinke Wang Rongqiao Wang Xiuchun Liu Kai Gao Jingli Sun Yong Yuan Lingwei Ma Hongchang Qian Dawei Zhang School of Energy and Power Engineering Beihang UniversityBeijing 100191China Beijing institute of Space Long March Vehicle Beijing 100076China National Materials Corrosion and Protection Data Center University of Science and Technology BeijingBeijing 100083China institute of Materials Intelligent technology Liaoning Academy of MaterialsShenyang 110004China Shanghai Spaceflight Precision Machinery institute Shanghai 201600China

The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal ***,limited studies have applied ACM to the corrosion protection properties of organic *** study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors,both applied on ACM sensors,to observe their corrosion protection properties over *** with artificial damage via scratches were exposed to immersion and alternating dry and wet environments,which allowed for monitoring galvanic corrosion currents in *** the corrosion tests,the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy *** trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface *** alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic *** with the blank epoxy coating,the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.

关键词： atmospheric corrosion monitoring technology corrosion inhibitor coating carbon steel corrosion protection

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

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 835-867页

作者： Sumaia Mohamed Elhassan Saad Mohamed Darwish Saleh Mesbah Elkaffas Department of Information technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of computing and Information technology Arab Academy for ScienceTechnology and Maritime TransportAlexandriaP.O.Box 1029Egypt

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic *** detection of lung tumors significantly increases the chances of successful treatment and ***,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung ***-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate ***,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor *** overcome these disadvantages,dual-model or multi-model approaches can be *** research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of *** automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung ***8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single *** is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to ***,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive *** combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applicati

关键词： Lung cancer detection dual-model deep learning technique data augmentation CNN YOLOv8