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Editorial for Machine learning and AI for underground metaverse

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Underground Space 2024年第6期19卷 1-3页

作者： Kok-Kwang Phoon Qiujing Pan Chong Tang information systems technology and design/Architecture and Sustainable design Singapore University of Technology and DesignSingapore 487372 School of Civil Engineering Central South UniversityChangsha 410075China State Key Laboratory of Coastal and Offshore Engineering Dalian University of TechnologyDalian 116024China

It is widely recognized that civil engineering practice,including underground construction,is lagging the fast pace digital transformation taking place in many *** key reason for this revolution is the emergence and convergence of digital technologies that include machine learning,artificial intelligence(AI),blockchain,cloud/edge computing,Internet of Things,5G communication,automation,digital twin,and *** parallel,Industry 4.0 is now complemented by Industry 5.0 that advocates a shift from economic value to societal value(sustainability,well-being,etc.).This means a shift from enterprises benefiting shareholders(profits)to stakeholders(people).

关键词： learning artificial underground

Pervasive Attentive Neural Network for Intelligent Image Classification Based on N-CDE’s

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Computers, Materials & Continua 2024年第4期79卷 1137-1156页

作者： Anas W.Abulfaraj department of information systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityRabigh21911Saudi Arabia

The utilization of visual attention enhances the performance of image classification *** attentionbased models have demonstrated notable performance,but many of these models exhibit reduced accuracy when confronted with inter-class and intra-class similarities and ***-Controlled Differential Equations(N-CDE’s)and Neural Ordinary Differential Equations(NODE’s)are extensively utilized within this ***’s possesses the capacity to effectively illustrate both inter-class and intra-class similarities and differences with enhanced *** this end,an attentive neural network has been proposed to generate attention maps,which uses two different types of N-CDE’s,one for adopting hidden layers and the other to generate attention *** distinct attention techniques are implemented including time-wise attention,also referred to as bottom N-CDE’s;and element-wise attention,called topN-CDE’***,a trainingmethodology is proposed to guarantee that the training problem is sufficiently *** classification tasks including fine-grained visual classification andmulti-label classification,are utilized to evaluate the *** proposedmethodology is employed on five publicly available datasets,including CUB-200-2011,ImageNet-1K,PASCAL VOC 2007,PASCAL VOC 2012,and MS *** obtained visualizations have demonstrated that N-CDE’s are better appropriate for attention-based activities in comparison to conventional NODE’s.

关键词： Differential equations neural-controlled DE image classification attention maps N-CDE’s

Olive Leaf Disease Detection via Wavelet Transform and Feature Fusion of Pre-Trained Deep Learning Models

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Computers, Materials & Continua 2024年第3期78卷 3431-3448页

作者： Mahmood A.Mahmood Khalaf Alsalem department of information systems College of Computer and Information SciencesJouf UniversitySakakahKingdom of Saudi Arabia department of information systems and technology Faculty of Graduate Studies and ResearchCairo UniversityGizaEgypt

Olive trees are susceptible to a variety of diseases that can cause significant crop damage and economic *** detection of these diseases is essential for effective *** propose a novel transformed wavelet,feature-fused,pre-trained deep learning model for detecting olive leaf *** proposed model combines wavelet transforms with pre-trained deep-learning models to extract discriminative features from olive leaf *** model has four main phases:preprocessing using data augmentation,three-level wavelet transformation,learning using pre-trained deep learning models,and a fused deep learning *** the preprocessing phase,the image dataset is augmented using techniques such as resizing,rescaling,flipping,rotation,zooming,and *** wavelet transformation,the augmented images are decomposed into three frequency *** pre-trained deep learning models,EfficientNet-B7,DenseNet-201,and ResNet-152-V2,are used in the learning *** models were trained using the approximate images of the third-level sub-band of the wavelet *** the fused phase,the fused model consists of a merge layer,three dense layers,and two dropout *** proposed model was evaluated using a dataset of images of healthy and infected olive *** achieved an accuracy of 99.72%in the diagnosis of olive leaf diseases,which exceeds the accuracy of other methods reported in the *** finding suggests that our proposed method is a promising tool for the early detection of olive leaf diseases.

关键词： Olive leaf diseases wavelet transform deep learning feature fusion

Enhancing Ulcerative Colitis Diagnosis:A Multi-Level Classification Approach with Deep Learning

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 1129-1142页

作者： Hasan J.Alyamani department of information systems Faculty of Computing and Information Technology in RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia

The evaluation of disease severity through endoscopy is pivotal in managing patients with ulcerative colitis,a condition with significant clinical ***,endoscopic assessment is susceptible to inherent variations,both within and between observers,compromising the reliability of individual *** study addresses this challenge by harnessing deep learning to develop a robust model capable of discerning discrete levels of endoscopic disease *** initiate this endeavor,a multi-faceted approach is embarked *** dataset is meticulously preprocessed,enhancing the quality and discriminative features of the images through contrast limited adaptive histogram equalization(CLAHE).A diverse array of data augmentation techniques,encompassing various geometric transformations,is leveraged to fortify the dataset’s diversity and facilitate effective feature extraction.A fundamental aspect of the approach involves the strategic incorporation of transfer learning principles,harnessing a modified ResNet-50 *** augmentation,informed by domain expertise,contributed significantly to enhancing the model’s classification *** outcome of this research endeavor yielded a highly promising model,demonstrating an accuracy rate of 86.85%,coupled with a recall rate of 82.11%and a precision rate of 89.23%.

关键词： Ulcerative colitis deep learning CLAHE transfer learning geometric transformations

A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

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Computers, Materials & Continua 2024年第6期79卷 4081-4105页

作者： Yasser Hachaichi Ayman E.Khedr Amira M.Idrees College of Computing and information technology at Khulais Department of Information SystemsUniversity of JeddahJeddah21959Saudi Arabia Faculty of Computers and information technology Future University in EgyptCairo11835Egypt

The diversity of data sources resulted in seeking effective manipulation and *** challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of *** of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search *** research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO *** the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain *** proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant *** confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve ***,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different *** proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

关键词： Optimization particle swarm optimization algorithm feature selection logistics supply chain management backlogs

Predicting Energy Consumption Using Stacked LSTM Snapshot Ensemble

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Big Data Mining and Analytics 2024年第2期7卷 247-270页

作者： Mona Ahamd Alghamdi Abdullah S.A.L-Malaise AL-Ghamdi Mahmoud Ragab information systems department Faculty of Computing and Information Technology(FCIT)King Abdulaziz University(KAU)Jeddah 21589Kingdom of Saudi Arabia information systems department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with School of EngineeringComputing and DesignDar Al-Hekma UniversityJeddah 22246Kingdom of Saudi Arabia information technology department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with Mathematics DepartmentFaculty of ScienceAl-Azhar UniversityNaser City 11884Egypt

The ability to make accurate energy predictions while considering all related energy factors allows production plants,regulatory bodies,and governments to meet energy demand and assess the effects of energy-saving *** energy consumption falls within normal parameters,it will be possible to use the developed model to predict energy consumption and develop improvements and mitigating measures for energy *** objective of this model is to accurately predict energy consumption without data limitations and provide results that are easily *** proposed model is an implementation of the stacked Long Short-Term Memory(LSTM)snapshot ensemble combined with the Fast Fourier Transform(FFT)and *** and Berard’s Individual Household Electric-Power Consumption(IHEPC)dataset incorporated with weather data are used to analyse the model’s accuracy with predicting energy *** model is trained,and the results measured using Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and coefficient of determination(R^(2))metrics are 0.020,0.013,0.017,and 0.999,*** stacked LSTM snapshot ensemble performs better than the compared models based on prediction accuracy and minimized *** results of this study show that prediction accuracy is high,and the model’s stability is high as *** model shows that high levels of accuracy prove accurate predictive ability,and together with high levels of stability,the model has good interpretability,which is not typically accounted for in ***,this study shows that it can be inferred.

关键词： energy consumption prediction Artificial Intelligence(AI) Deep Learning(DL) snapshot ensemble

Microstructure transformations and improving wear resistance of austenitic stainless steel additively fabricated by arc-based DED process

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Defence technology（防务技术） 2024年第8期38卷 194-204页

作者： Ashish Yadav Manu Srivastava Prashant K.Jain Sandeep Rathee Hybrid Additive Manufacturing Laboratory Mechanical Engineering DepartmentPDPM Indian Institute of Information TechnologyDesign&ManufacturingJabalpur482005Madhya PradeshIndia FFF Laboratory Mechanical Engineering DepartmentPDPM Indian Institute of Information TechnologyDesign&ManufacturingJabalpur482005Madhya PradeshIndia department of Mechanical Engineering National Institute of TechnologySrinagarIndia

In this study, austenitic stainless steel(ASS) was additively fabricated by an arc-based direct energy deposition(DED) technique. Macrostructure, microstructure, mechanical characteristics at different spatial orientations(0°, 90°, and 45°), and wear characteristics were evaluated at the deposited structure top, middle, and bottom regions. Results show that austenite(γ) and delta-ferrite(δ) phases make up most of the microstructure of additively fabricated SS316LSi steel. Within γ matrix, δ phase is dispersed both(within and along) grain boundaries, exhibiting a fine vermicular morphology. The bottom, middle,and top regions of WAAM deposited ASS exhibit similar values to those of wrought SS316L in the tensile and impact test findings. Notably, a drop in hardness values is observed as build height increases. During SEM examinations of fractured surfaces from tensile specimen, closed dimples were observed, indicating good ductility of as-built structure. Wear test findings show signs of mild oxidation and usual adhesive wear. By depositing a mechanically mixed composite layer, an increase in the oxidation percentage was discovered to facilitate healing of worn surfaces. The findings of this study will help in design, production and renovation of products/components that are prone to wear. WAAM-deposited ASS has remarkable strength and ability to withstand impacts;it can be used in the production of armour plates for defence applications, mainly military vehicles and aircraft.

关键词： Metal additive deposition Defence applications Arc-based DED Characterization Wear behaviour Fractography

Size effects of polydopamine-coated BaTiO_(3) nanoparticles on the piezoelectric performance of P(VDF-TrFE)/BaTiO_(3) composite

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Journal of Materiomics 2024年第4期10卷 857-869页

作者： Hyeokjun Si Donghyun Lee Donghyuck Park Jeonghoon Oh Junseo Gu Inje Lee Kwanlae Kim department of Manufacturing systems and design Engineering(MSDE) Seoul National University of Science and Technology(SeoulTech)Seoul01811Republic of Korea

The size effect of the polydopamine(PDA)-coated BaTiO_(3)(BTO)(BTO@PDA)nanoparticles(NPs)on the interfacial compatibility between BTO NPs and the polymer matrix and the resultant piezoelectric performance of the composite films remain *** this study,BTO and BTO@PDA NPs of various sizes were incorporated into a P(VDF-TrFE)matrix to prepare two series of P(VDF-TrFE)/BTO and P(VDF-TrFE)/BTO@PDA ***,the effects of the NP size on the dielectric,ferroelectric,and piezoelectric properties of the composite films were comprehensively *** the size of the BTO@PDA NPs increased,residual hole defects were clearly observed in the cross section of the composite *** deteriorated interfacial compatibility due to the large size of the BTO@PDA NPs was also confirmed by the increased dielectric permittivity of the composite film,which was induced by the intensified interfacial *** P(VDF-TrFE)/BTO@PDA composite with NPs of the smallest size(100 nm)exhibited superior piezoelectric performance owing to the excellent interfacial compatibility between the fillers and the *** piezoelectric performance was significantly enhanced by the reduced leakage current during electrical poling and reduced trap ***,the pulse waveform originating from the radial artery was precisely measured using the optimised P(VDF-TrFE)/BTO@PDA composite film.

关键词： Barium titanate and titanates Piezoelectric properties Composites Sensors

Survey and Prospect for Applying Knowledge Graph in Enterprise Risk Management

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Computers, Materials & Continua 2024年第3期78卷 3825-3865页

作者： Pengjun Li Qixin Zhao Yingmin Liu Chao Zhong Jinlong Wang Zhihan Lyu School of information and Control Engineering Qingdao University of TechnologyQingdao266520China department of Game design Uppsala UniversityVisby62167Sweden

Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market *** the challenges posed by intricate and unpredictable risk factors,knowledge graph technology is effectively driving risk management,leveraging its ability to associate and infer knowledge from diverse *** review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business ***,employing bibliometric methods,the aim is to uncover the developmental trends and current research hotspots within the domain of enterprise risk knowledge *** the succeeding section,systematically delineate the technical methods for knowledge extraction and fusion in the standardized construction process of enterprise risk knowledge *** comparing and summarizing the strengths and weaknesses of each method,we provide recommendations for addressing the existing challenges in the construction ***,categorizing the applied research of enterprise risk knowledge graphs based on research hotspots and risk category standards,and furnishing a detailed exposition on the applicability of technical routes and ***,the future research directions that still need to be explored in enterprise risk knowledge graphs were discussed,and relevant improvement suggestions were *** and researchers can gain insights into the construction of technical theories and practical guidance of enterprise risk knowledge graphs based on this foundation.

关键词： Knowledge graph enterprise risk risk identification risk management review